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Selected Topics in Network Design

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Selected Topics in Network Design

Course Objectives

        • To provide a broad overview of some advanced wireless networks including their architectures and design issues pertaining to link layer and network layer
        • To develop mathematical skills to analyze some of the network design issues
  • To develop design fundamentals which can help students to take up projects in wireless networking

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Selected Topics in Network Design

Course Outcomes

  • Understand the fundamentals of wireless networks
  • Design simple protocols for wireless networks
  • Apply link access technique according to the network architecture
  • Analyze the design issues in wireless networks
  • Develop ideas for pursuing student projects in wireless networking domain

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Course Content

Unit 1 - Introduction

  1. Wireless channel characteristics, Wireless networking fundamentals, Wireless network architectures, Wireless networking standards
  2. Wireless protocols: Link layer, Network layer and Transport layer.

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Course Content

Unit 2 - Network Design and Analysis

  1. Defining system model: Decision variables, constants, objectives and constraints; Simulating data packet arrivals and random variables for various propagation models, Problem formulation/algorithm
  2. Fundamentals of Markov chains, Analysis using Markov chains,
  3. Basics of Optimization

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Course Content

Unit 3 -  Cognitive Radio Networks

  1. Concepts, Spectrum sensing, Cooperative spectrum sensing, Dynamic spectrum access, Network architectures: Centralized and distributed, multichannel allocation problem, multihop communication, QoS; Design and analysis examples.

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Course Content

Unit 4 – Next Generation Wireless Networks

  1. LTE and LTE-A fundamentals, Radio specifications, Frame format, Design and analysis of LTE-A Resource Allocation Problems;
  2. Overview of 5G networks: Cloud RAN, Small scale heterogeneous networks (HetNets), Wireless backhaul networks;
  3. Design and Analysis of 5G Resource Allocation Problems.

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Course Content

Unit 5 - Other Ad hoc Networks

  1. Sensor networks: Applications, Challenges, Network architecture, Link layer and routing issues
  2. VANETs: Applications, IEEE 802.11p standard, Link layer issues, WAVE specification, Design and analysis examples: MAC protocols for VANETs
  3. Wireless personal area networks (Bluetooth and Zigbee): PHY, MAC and message format

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Selected Topics in Network Design

Introduction

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Channel Characteristics

SELECTED TOPICS IN NETWORK DESIGN

What is a wireless spectrum?

  • Wireless radio spectrum ranges from 900 MHz to 5 GHz

  • Wireless radio spectrum is classified as licensed and unlicensed bands
  • Licensed bands are bought by private operators (e.g., cellular operators, FM station) or authorized by the government (e.g., military, public safety, satellite)

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What is a wireless spectrum?

  • Spectrum usage guidelines are given by International Telecommunication Union Radiocommunication (ITU-R)
  • Govt. bodies give recommendations for wireless spectrum usage in a given region based on the ITU-R guidelines
    • Examples: India (TRAI), US (FCC), UK (OFCOM)
  • Some international bodies are involved in standardizing the spectrum usage and wireless device design
    • Examples: IEEE, ETSI, WiFi Alliance, etc.
  • Wireless communication is more challenging compared to wired communication as the transmitted signal undergoes scattering, reflection and diffraction.

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Wireless Channel Characteristics

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What is a wireless channel?

  • Wireless channel refers to a logical communication path between a sender and a receiver over a to a band of frequencies
  • Wireless channel capacity (throughput) depends on the bandwidth, operating frequency, transmit power, distance, obstacles, environment, time of use, number of contenders
  • The amplitude and phase of the received signal are affected by the above factors
  • The received signal exhibits random characteristics which can be described statistically

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How are wireless channels accessed?

  • Wireless channels can be shared or exclusively assigned

  • Wireless channels are shared using link layer protocols (i.e., channel sensing and random access)
  • Wireless channels are exclusively assigned using central controller (i.e., scheduled using base station)
    • Exclusive access is achieved by multiple access techniques

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Selected Topics in Network Design

Introduction – Wireless Channel Characteristics

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Channel Characteristics

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What is free space path loss?

  • In an ideal environment, the received power varies according to the wavelength and the distance between the transmitter and the receiver

  • Here, d0 is between 1-10 m indoors or 10-100 m outdoors
  • In the above scenario, the difference between the transmit power (dB) and received power (dB) is referred to as free space path loss (denoted by K).

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What is free space path loss?

  • Received power due to general path loss, factoring different settings (e.g., urban, without LOS, etc.) is given by

  • Here, ϒ is called path loss exponent

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Free space path loss: Example #1

  • If a unity gain antenna transmits 50 W power at 900 MHz carrier frequency, find the received power (dBm) at a reference distance of 100 m from the transmitter. Compare received power with transmit power. What is the received power at 10 km?
  • Solution:
  • Here, d0 = 100 m

  • Expressed in dBm, we get

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Free space path loss: Example #1

  • Solution:
  • Here, d = 10 km and ϒ = 2

  • Note that

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Wireless Channel Characteristics

SELECTED TOPICS IN NETWORK DESIGN

What is range?

  • Let Smin denote the receiver sensitivity (minimum detectable signal strength), then using Frii’s equation we get the range dmax

      • Coverage area (range) is defined as the percentage of area in a cell which has the SNR above some minimum.

      • Here, kT0B is referred to as thermal noise of ideal receiver
      • B is bandwidth and NF is noise figure

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Wireless Channel Characteristics

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What is fading?

    • Obstacles between the transmitter and receiver cause scattering, reflection and diffraction of the transmitted signal
      • Reflected signals take longer path than line-of-sight (LOS) signal.
        • Hence, the reflected signals arrive after delays
    • The delayed copies of the transmitted signal arrive either in phase or out of phase with one another.
    • This causes the received signal strength to fluctuate. This is referred to as fading.

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What is fading?

    • In a mobile-radio environment, each reflected signal has its own Doppler shift, time delay, and path attenuation, and multipath propagation results in a time-varying signal as the mobile moves position
    • Such a channel is linear, but time-varying
    • Doppler shift means changes (increases or decreases) in the carrier frequency
    • The number of multipath signals received in a given time slot will vary
    • The inter-arrival times between multipath signals can also vary

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Wireless Channel Characteristics

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What is fading?

      • The Doppler shift is given by

      • Here, v is velocity and 𝜃 is angle of incidence of the received signal
      • Different types of fading occur based on the direction of motion and area over which the motion occurs
      • Next, we see small scale fading (or multipath fading) followed by large scale fading (or shadowing)

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Wireless Channel Characteristics

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What is small scale fading (multipath fading)?

    • Small scale fading refers to the rapid changes of the amplitude and phase of a radio signal over a short period of time (on the order of seconds) or a short distance (a few wavelengths)
    • When no LOS is involved, the statistics of the channel fluctuations follows Rayleigh distribution
    • When LOS is involved, the statistics of the channel fluctuations follows Rician distribution
    • Multipath fading can be classified as flat (wide band) or frequency selective (narrow band) depending on the observed statistics over the channel bandwidth and over the bandwidth occupied by the transmitted signal

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What is small scale fading (multipath fading)?

    • Multipath fading can be classified as fast or slow depending on the observed statistics over the symbol period of the transmitted signal
    • The classifications based on statistics observed over time and bandwidth are independent

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What is large scale fading (shadowing)?

    • It represents the average signal-power attenuation (i.e., path loss) due to motion over large distances (several 100s or 1000s of meters)
    • It is impacted by terrain configuration between the transmitter and receiver
    • Examination of the power over such a distance reveals that the power fluctuates around a mean value and these fluctuations have a rather long period.
  • The statistics of large-scale fading are log-normally distributed with 𝜎 of 4-13 dB for outdoor channels

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Wireless Channel Characteristics

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Effect due to path loss, multipath fading and shadowing

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Wireless Channel Characteristics

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Effect due to path loss, multipath fading and shadowing

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Wireless Channel Characteristics

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Achievable data rate

    • Capacity or achievable data rate (C) is expressed by Shannon formula
    • When wireless channels are orthogonally assigned, no interference occurs
    • When wireless channels are shared, interference occurs

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Selected Topics in Network Design

Introduction – Networking Fundamentals

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Networking Fundamentals

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What is wireless networking?

  • Wireless networking deals with data transmission over wireless medium

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Networking Fundamentals

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What is wireless networking?

  • Wireless networking deals with data transmission over wireless medium

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Networking Fundamentals

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What is wireless networking?

  • Partly or entirely, the communication path between the sender-receiver pair consists of wireless links and switches/routers
  • Wireless medium affects each sub-task under the data communication process
    • A typical data communication process is depicted logically into a set of layers referred to as the TCP/IP protocol stack
  • Thus, the operations of the upper layers must be adapted in response to the unreliable wireless medium

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Recap of TCP/IP protocol stack

  • Data is generated and formatted by the application layer
  • Transport layer deals with segmentation and reassembly of large data packets. Can supports reliable data transfer (QoS)
  • Network layer deals with moving the data packets towards the destination using IP
  • Link layer deals with delivering packets across each link by overcoming packet collision
  • Physical layer encodes the data to minimize bit errors at the destination node.
  • Sender and receiver follow top down and bottom up approach respectively

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Role of PHY layer in wireless networks

  • Deals with
    • Choice of modulation and coding scheme based on SNR measurements
    • minimizing bit-error
    • transmit power control
    • usage of antennas

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Role of link layer in wireless networks

  • Deals with
    • Resource allocation
    • Improving link utilization
    • Interference management
    • Link access techniques
    • Frame format (control overhead and data)
  • The above issues can be addressed using
    • Innovative network architectures
    • Scheduling algorithms
    • Optimization / Machine learning / Game theory

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Networking Fundamentals

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Role of network layer in wireless networks

  • Deals with
    • IP addressing in mobile environment
    • Routing of packets in foreign (visited) network
    • Route discovery and route reconfiguration in wireless ad hoc networks
  • The above issues can be addressed using
    • Mobile IP protocols
    • Indirect routing
    • Distance vector based routing protocols

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Role of transport layer in wireless networks

  • Deals with
    • Handoff and retransmissions caused by unreliable wireless medium
    • Preserve end-to-end principle across wireless and wired medium
  • The above issues can be addressed using
    • Indirect TCP
    • Snooping TCP
    • Mobile TCP

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Networking Fundamentals – Link Layer

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Resource allocation in wireless networks

  • Implemented either using guaranteed access techniques or random access techniques

What is guaranteed access?

  • Information is collected from all end-users over a common control channel by a central controller
  • Scheduling algorithm is implemented based on the available resources and end-users’ information
  • Results of the scheduling algorithm are broadcast
  • End-users access the wireless medium as per the results
  • All the above steps are scheduled periodically (aka frame)
  • Quality of service can be guaranteed

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Networking Fundamentals – Link Layer

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Examples of guaranteed access – TDMA

  • Time is slotted and assigned to end-users

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Networking Fundamentals – Link Layer

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Examples of guaranteed access – TDMA (contd.)

  • Information about slot assignment is broadcast periodically
  • Size of the TDMA frame can be adjusted by the central controller to achieve QoS
  • TDMA frame can be divided into uplink subframe and downlink subframe
  • Synchronization in time domain is challenging
  • Guard time needed to avoid multipath propagation

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Networking Fundamentals – Link Layer

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Examples of guaranteed access – FDMA

  • Bandwidth is slotted and assigned to end-users

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Networking Fundamentals – Link Layer

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Examples of guaranteed access – FDMA (contd.)

  • Information about slot assignment is broadcast periodically
  • Frequency bands can be divided into uplink and downlink bands
  • If separate uplink and downlink is assigned to a user per frame, it is referred to as full duplex
    • Otherwise, it is referred to as half duplex
  • Filtering in frequency domain is challenging
  • Guard band needed to avoid inter-symbol interference

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Networking Fundamentals – Link Layer

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Examples of guaranteed access – CDMA

  • Unique wideband orthogonal codes assigned to end-users
  • All end users can be active in the same time and frequency
  • Complex receiver, needs more complicated power control

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Networking Fundamentals – Link Layer

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Other notable guaranteed access schemes:

  • Polling; Token passing ring; Combining TDMA and FDMA (e.g., FHSS, OFDMA)

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Random access schemes

  • Link layer protocols (MAC protocols) are required for wireless channel access
  • No control controller so end-users independently access the wireless channel
  • Packet collisions occur due to simultaneous transmissions
  • Link layer protocols address the hidden node and exposed node problems
  • Hidden node problems reduce throughput due to packet collisions
  • Exposed node problems reduce throughput due to loss of transmission opportunities

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Networking Fundamentals – Link Layer

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Carrier sense multiple access – CSMA

  • Sender generates DATA and senses the wireless channel for transmission
  • If channel is busy, sender performs backoff (i.e., defers sensing)
  • If channel is idle, sender transmits DATA and waits for acknowledgement (ACK)
  • If ACK is received, then sender had successful transmission
  • If ACK is not received, then packet is assumed to be lost
  • Packet loss occurs either due to simultaneous transmission (referred to as collision) or due to signal fade or receiver is busy

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Networking Fundamentals – Link Layer

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Hidden node problem

  • Senders not in range of one another but have common receiver

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Networking Fundamentals – Link Layer

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Hidden node problem (contd.)

    • A and C perform carrier sensing and detect an idle channel
    • Both A and C transmit to B and this results in packet collision
    • A and C are said to be hidden from each other
    • CSMA can be altered to overcome hidden terminal problem by channel reservation via control messages

A

B

C

Hidden nodes reduce throughput due to collisions

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Networking Fundamentals – Link Layer

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Exposed node problem

    • F senses the channel and starts transmission to E after sensing it to be idle
    • G wants to transmit to H but senses the channel busy due to F’s transmission
    • G is said to be exposed to F’s transmission
    • CSMA can be altered to overcome hidden terminal problem by channel reservation via control messages

E

F

G

H

Exposed nodes reduce throughput due to loss of transmission opportunity

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Selected Topics in Network Design

Introduction – IEEE 802.11 Architecture, PHY and MAC

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Networking Fundamentals – Link Layer

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IEEE 802.11 – Architecture

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Networking Fundamentals – Link Layer

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IEEE 802.11 – Architecture (contd.)

    • A basic service set (BSS) can be either operate in infrastructure mode or ad hoc mode
    • A distribution system connects several BSSs via the AP to form a single network and thereby extends the wireless coverage area. This gives rise to extended BSS
    • Stations can select an AP and associate with it
    • The APs support roaming, the distribution system handles data transfer between the different APs.
    • APs provide synchronization within a BSS, support power management, and can control medium access to support time-bounded service

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Networking Fundamentals – Link Layer

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IEEE 802.11 – Protocol architecture

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Networking Fundamentals – Link Layer

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IEEE 802.11 – PHY

  • Channel allocation in IEEE 802.11
  • 2.4 GHz to 2.485 GHz divided into 11 overlapping channels of 85MHz each.
  • Channels 1, 6 and 11 are chosen for channel assignment
  • Each WiFi access point is associated with one unique channel
  • Either FHSS or DSSS or OFDMA is used on the channel

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Networking Fundamentals – Link Layer

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IEEE 802.11 – MAC

  • First of all, it has to control medium access, but it can also offer support for roaming, authentication, and power conservation.
  • The basic services provided by the MAC layer are the mandatory asynchronous data service and an optional time-bounded service.
  • The asynchronous service supports broadcast and multi-cast packets, and packet exchange is based on a ‘best effort’ model, i.e., no delay bounds can be given for transmission

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Networking Fundamentals – Link Layer

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IEEE 802.11 – MAC (contd.)

  • The asynchronous data service is called distributed coordination function (DCF) and the optional time bounded service is called point coordinated function (PCF)
  • Only DCF is supported in ad hoc mode whereas both DCF and PCF are supported in infrastructure mode
  • Together the DCF and the PCF are called distributed foundation wireless medium access control (DFWMAC).
  • DCF is discussed under two schemes
    • Basic access scheme (CSMA/CA)
    • DCF with RTS/CTS

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Networking Fundamentals – Link Layer

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IEEE 802.11 – Basic access scheme (CSMA/CA)

    • If channel is idle, wireless station waits for DIFS duration
    • Transmit DATA packet
    • If transmission was successful, the receiver sends an ACK after SIFS duration

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Networking Fundamentals – Link Layer

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IEEE 802.11 – Basic access scheme (contd.)

    • If ACK is received then the transmission is considered successful by sending wireless station
    • If collisions occur, then binary exponential backoff is initiated

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IEEE 802.11 – Basic access scheme (contd.)

    • Retransmission occurs after randomly chosen delay
    • Probability of choosing a random delay decreases with collision

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Networking Fundamentals – Link Layer

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IEEE 802.11 – DCF with RTS/CTS

  • If channel is idle then wait for DIFS interval
    • Randomly choose a backoff value k and start decrementing it
    • When k=0, transmit RTS and wait for CTS from receiver

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Networking Fundamentals – Link Layer

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IEEE 802.11 – DCF with RTS/CTS (contd.)

    • If CTS is received after SIFS duration then transmit DATA
        • Others defer their transmission based in NAV carried in RTS and CTS packet

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IEEE 802.11 – DCF with RTS/CTS (contd.)

    • If transmission was successful, receiver sends ACK after SIFS
    • If ACK is received the sender has successfully transmitted

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How hidden nodes resolved using DCF with RTS/CTS?

    • Suppose A transmits RTS and B replies with CTS then C will receive the CTS of B and hence defers the transmission
    • Suppose A and C transmit RTS simultaneously and so packet collision occurs.
      • Binary exponential helps in reducing collision again

A

B

C

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What should end-user experiencing packet collision do under DCF with RTS/CTS?

    • They double their backoff window and choose a new backoff value. This is referred to as binary exponential backoff.

What should users not experiencing packet collision but waiting for transmission do?

    • They simply freeze their backoff values till next DIFS idle time. Then, they resume decrementing their backoff value.

What does a sender do after successful transmission?

    • A sender after successful transmission will reset its backoff window to initial size w and choose a new value of k.

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Example scenario of DCF with RTS/CTS

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Selected Topics in Network Design

Introduction – IEEE 802.11

Frame structure, Network Admission & Roaming and Standards

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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IEEE 802.11 Frame Structure

SELECTED TOPICS IN NETWORK DESIGN

IEEE 802.11: Frame structure

  • Frame control: The first 2 bytes serve several purposes. It has several sub fields
    • Protocol version: 2 bit field currently has value 00
    • Type: The type field determines the function of a frame: management (=00), control (=01), or data (=10). The value 11 is reserved.

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure (contd.)

    • Subtype:

0000

User (data or association request)

1000

Beacon

1011

RTS

1100

CTS

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure (contd.)

    • More fragments: Set to 1 if more segments are to follow
    • Retry: Set to 1 if data is retransmitted
    • Power Management: Set to 1 indicates if going to sleep mode; Set to 0 means active

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IEEE 802.11: Frame structure (contd.)

    • More data: To indicate a receiver that a sender has more data to send than the current frame. This can be used by an access point to indicate to a station in power-save mode that more packets are buffered.
    • WEP: This field indicates that the standard security mechanism of 802.11 is applied

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IEEE 802.11: Frame structure (contd.)

    • Order: To indicate a receiver that frames are processed in strict order

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure (contd.)

  • Duration: Indicates the time for which the medium will be busy due to data transmission
  • Sequence control: Used to distinguish duplicate transmissions
  • CRC: 32 bit code for error detection

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure (contd.)

  • Address fields: Address 1 denotes receiver’s MAC address, Address 2 denotes sender’s MAC address, Address 3 and Address 4 are used for logical assignment of frames (logical sender, BSS identifier, logical receiver)

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure (contd.)

    • To/from DS

Ad hoc mode

Infrastructure mode

(intra BSS)

Infrastructure mode

(inter BSS)

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IEEE 802.11 Frame Structure

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IEEE 802.11: Frame structure – Control packets

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IEEE 802.11 Network Admission and Roaming

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Network admission & roaming

  • Connection setup between a wireless node and AP under IEEE 802.11 architecture
      • Active scanning or passive scanning
      • Authorization phase
      • Association phase
      • Data exchange phase

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IEEE 802.11 Network Admission and Roaming

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Active and passive scanning

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IEEE 802.11 Standards

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History and evolution

  • First Wi-Fi standard called IEEE 802.11-1997
  • IEEE 802.11b (1999) operated on 2.4 GHz, supported 11 Mbps, based on DSSS, cheaper router, susceptible to interference
  • IEEE 802.11a (1999) operated on 5 GHz, supported 54 Mbps, introduced OFDM, not a commercial success
  • IEEE 802.11g (2003) operated on 2.4 GHz, supported 54 Mbps, backward compatible with IEEE 802.11b
  • IEEE 802.11n aka Wi-Fi 4 (2009) operated on both 2.4 GHz and 5 GHz, supports 300-450 Mbps, used MIMO

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IEEE 802.11 Standards

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History and evolution (contd.)

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Selected Topics in Network Design

Introduction – Network layer challenges and solutions – Part 1

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Network Layer Challenges and Solutions

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Challenges in WWAN due to mobility

  • IP address is subnet dependent and usually assigned by DHCP
  • Mobility can lead to a wireless device traversing multiple subnets
  • Change of IP address causes service disruption
  • Keeping initial IP address permanent during the mobility leads to routing issues
  • Scalability is and important issue to be addressed

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Network Layer Challenges and Solutions

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Mobile IP: Introduction

  • A set of protocols to ensure IP addressing, routing and packet forwarding in WWAN
  • Mobile IP simplifies the network layer challenges due to mobility
  • No need to update all routers between the sender and mobile receiver
  • No need to update the sender about the mobility of the receiver
  • Components of Mobile IP
    • Agent discovery for mobile users
    • Registration of mobile user
    • Indirect routing of datagrams

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Network Layer Challenges and Solutions

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Mobile IP: Terminology

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Network Layer Challenges and Solutions

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Mobile IP: Terminology (contd.)

  • Mobile node (MN): An end-system or router that can change its point of attachment to the internet using mobile IP. The MN keeps its IP address and can continuously communicate from any location

  • Correspondent node (CN): The partner node with which the MN communicates. The CN can be a fixed or mobile node.

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Network Layer Challenges and Solutions

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Mobile IP: Terminology (contd.)

  • Home network: It is the subnet the MN belongs to with respect to its IP address. No mobile IP support is needed within the home network.

  • Foreign network: The foreign network is the current subnet the MN visits and which is not the home network.

  • Home agent: A router on a mobile node’s home network which delivers datagrams to departed mobile nodes, and maintains current location information for each.

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Network Layer Challenges and Solutions

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Mobile IP: Terminology (contd.)

  • Foreign agent: A router on a mobile node’s visited network which cooperates with the home agent to complete the delivery of datagrams to the mobile node while it is away from home.

  • Home address: An IP address that is assigned for an extended period of time to a mobile node. It remains unchanged regardless of where the node is attached to the Internet.

  • Care-of-address: It is the address associated with the MN when it is away from its home network

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Network Layer Challenges and Solutions

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Mobile IP: Operations

  • Agent discovery
    • Agent advertisement
    • Agent solicitation
  • Registration of care-of-address
  • Routing of datagrams to mobile node

  • Impact of the above operations:
  • The above operations do not require update of routing tables across the internet
  • The home agent is the most crucial part of the setting up and running the mobile IP protocols
  • The CN is oblivious of the change of location of the MN

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Network Layer Challenges and Solutions

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Mobile IP: Agent discovery – Agent advertisement

  • Foreign agents and home agents advertise their presence periodically using special agent advertisement messages

ICMP message according to RFC 1256 + extended mobility

Shaded part is the advertisement

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Network Layer Challenges and Solutions

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Mobile IP: Agent discovery – Agent advertisement

IP header values

TTL is set to 1

Destination IP address is either 224.0.0.1 (multicast) or 255.255.255.255 (broadcast)

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Network Layer Challenges and Solutions

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Mobile IP: Agent discovery – Agent advertisement

ICMP part

Type = 9 / 16; Code = 0

#address gives no. of advertised addresses

Addresses are shown below

Lifetime tells valid time

Preference gives readiness of agent

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Agent discovery – Agent advertisement

Extended mobility part

Type = 16; length = 6 + 4 × (No. of COA)

sequence number gives the total number of advt. sent so far

registration lifetime gives max. time of a requested COA

COA: offered address

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Agent discovery – Agent advertisement

Extended mobility part

R: Agent reg. required even when using colocated COA

B: Agent busy to accept reg. requests

H: Home agent

F: Foreign agent

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Agent discovery – Agent advertisement

Extended mobility part

M and G: Minimal encapsulation or generic routing encapsulation

r: set to zero

T: Indicates reverse tunnelling by FA

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Agent discovery – Agent solicitation

  • Agent solicitation message is sent by MN if it has not received an agent advt. or inter-arrival time is too high
  • Typically, an MN can send out three solicitations, one per second, as soon as it enters a new network
  • If an MN does not receive an answer to its solicitations it must decrease the rate of solicitations exponentially
  • Once an MN receives the agent advt., it enters the registration phase.

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Selected Topics in Network Design

Introduction – Network layer challenges and solutions – Part 2

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: COA registration process

  • After performing the agent discovery, the MN receives the COA in the foreign network
  • The next step is to inform the HA about the COA
  • This will enable routing of packets to the MN using the COA
  • Next we see the registration process

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: COA registration process (contd.)

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration request message

  • The message is carried as UDP segment with port number 434
  • The IP header source address is that of the MN, destination address is that of FA or HA

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration request message (contd.)

  • Type is set to 1 for registration request
  • S is used to indicate whether HA prior mobility bindings must be retained or not
    • This allows simultaneous bindings

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration request message (contd.)

  • S bit is used t indicate whether MN wants broadcasts in the home network
  • Using D bit, MN can indicate whether it wants to manage encapsulation itself

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration reply message

  • Lifetime indicates the validity of the registration in seconds
  • The home address is the fixed IP address of the MN
  • home agent is the IP address of the HA
  • COA represents the tunnel endpoint.

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration reply message (contd.)

  • 64 bit identification is generated by the MN to identify a request and match it with registration replies
  • Extensions contain parameters for authentication
  • Type = 3 and code indicate the result of the registration

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Registration reply message (contd.)

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Routing of datagrams

  • Following the successful registration of the COA with the HA, the MN can start receiving datagrams
  • The datagrams are encapsulated before delivery to the MN by the HA
  • The FA / MN decapsulate the packet in the foreign network
  • The MN simply replies back to the CN using the source address in the received packet and using its home address for the destination
  • See triangle or indirect routing next

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Network Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Mobile IP: Routing of datagrams

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Selected Topics in Network Design

Introduction – Transport layer challenges and solutions

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Recap of TCP in fixed networks

  • Timeout indicates congestion in the network
  • Packets can get corrupted during switching operation
  • TCP reacts to timeout by retransmitting the old packet
  • Transmission rate is deflated upon experiencing timeout
  • Throughput suffers due to congestion
  • Transmission rate increases with successful acknowledgements
  • Congestion control algorithm uses slow start, congestion avoidance and fast retransmit (optional) to improve the throughput

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Implications of mobility on TCP

  • Slow start is not suited for wireless and mobile environments mobility
  • Wireless medium can cause packets to become corrupted
  • Timeouts can occur due to signal fading
    • Link layer also reacts to frequent disruptions
  • Timeouts can occur during handoff between foreign agents
  • Foreign agents may not buffer packets and exchange them during handoff
  • All the above issues can lead to TCP retransmissions

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP

  • Two separate TCP connections: one on wired and the other on wireless
  • Access point acts as proxy for the mobile host

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP (contd.)

  • Other possibility for partitioning TCP is the foreign agent of the mobile IP which controls mobility
  • Access point buffers and detects packet loss on wired and wireless separately

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP (contd.)

  • Access point acknowledges successful transmissions and retransmits lost packets separately on wired and wireless
  • Access point isolates packet loss on wireless from wired

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP Handoff

  • When mobile host performs handoff, the old access point transfers all buffered data and TCP parameters with respect to both wired and wireless to the new access point
    • Fixed host does not know about the mobility

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP Advantages

  • No changes in TCP algorithms
  • Transmission errors on wireless not propagated into wired
  • Testing of new TCP solutions easy
    • Different protocols or different optimization can be applied on wired and wireless (e.g., data compression)
  • Round trip in wireless is assumed very small

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Indirect TCP Disadvantages

  • Violates TCP end-to-end principle
  • Latency during handoff (higher transmission delay)
  • Foreign agent must be trusted entity. If transport layer security is applied then I-TCP will not work

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP

  • Best place to enhance TCP is at the foreign agent of mobile IP
  • The foreign agent buffers all packets with destination mobile host

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP (contd.)

  • Additionally snoops the ongoing TCP transmissions in both directions
  • Foreign agent can perform fast retransmission to mobile host when packet loss / duplicate ACKs are detected on the wireless

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP (contd.)

  • Foreign agent does not acknowledge the correspondent host
  • Foreign agent can avoid unnecessary retransmissions by mobile host by removing duplicate ACKs from wired side

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP (contd.)

  • If packet loss is detected in the transmissions to correspondent host then NACK is sent by foreign agent to the mobile host
  • Reordering of packets is done by mobile host automatically

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP Advantages

  • End-to-end semantics are preserved
  • The correspondent host does not need to be changed; most of the enhancements are in the foreign agent
  • The correspondent host does not need to be changed; most of the enhancements are in the foreign agent

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Snooping TCP Disadvantages

  • Errors from wireless propagate into wired part
  • NACK usage requires additional requirements for mobile host
  • All efforts at snooping and buffering are useless if TCP header encryption is used.

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Mobile TCP

  • For handling of lengthy and/or frequent disconnections
  • I-TCP + S-TCP + adapt to lengthy/frequent disconnections
  • Unmodified TCP between SH and CH and adaptive (optimized) TCP between MH and SH
  • SH monitors the transmissions but does not buffer data

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Mobile TCP (contd.)

  • SH monitors all packets sent to the MH and all ACKs sent by the MH
  • If ACKs are not detected then SH assumes disconnection of MH
  • Sender is choked upon detecting disconnection of MH
    • Sender window goes to zero

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Mobile TCP (contd.)

  • Upon detecting reconnection with MH, the sender window is restored to old value
    • So no slow start due to disconnection
  • Other issues of TCP remain unaffected
    • Retransmissions are carried out by original sender

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Transport Layer Challenges and Solutions

SELECTED TOPICS IN NETWORK DESIGN

Solutions – Mobile TCP Advantages

  • Maintains end-to-end semantics of TCP
  • If the MH is disconnected, it avoids useless retransmissions, slow starts or breaking connections
  • No buffering of data and transfer during handoff

Solutions – Mobile TCP Disadvantages

  • Assumes low bit error rate on wireless link
  • SH does not act as proxy for MH so errors from wireless propagates into wired
  • Upgrade of MH software to be adaptive

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Selected Topics in Network Design

Introduction – Wireless Network Architectures and Standards

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

126 of 553

Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks

  • Composed of wireless devices (terminals, access points, switches, routers, etc.) connected by wireless links
  • Can consist of fixed wired terminals
  • Wireless networks can be classified based on the topology, span, architecture, link access method and application
  • Network design issues depend on the above classification
  • Some common objectives of network design are:
    • maximizing throughput, minimizing access delay, maximizing energy efficiency, maximizing spectral efficiency, etc.

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Examples

  • WiFi
  • Bluetooth and Zigbee
  • WiMAX
  • Cellular network (3G, 4G, 5G)
  • Satellite communication network
  • Vehicular network
  • Heterogeneous network

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks - Topologies

  • Network topology refers to the physical configuration of links between the wireless devices (e.g., terminals, switches, routers)
  • Examples: Star, bus, mesh, ring, tree, ad hoc, etc.

Star topology is seen in WiMAX, Bluetooth, Zigbee, WiFi, etc.

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Topologies (contd.)

Mesh networks, also known as mobile ad hoc networks (MANETs), are local or metropolitan area networks in which nodes are mobile and communicate directly with adjacent nodes without the need for central controlling devices

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Topologies (contd.)

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Topologies (contd.)

Wireless NIC

Wireless access point

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Span

  • Based on the range and application of the wireless network, we have
    • WBAN
    • WPAN
    • WLAN
    • WWAN
    • WMAN
  • Coverage area or range is also called cell
  • Alternative names given based on cell size
    • Femtocell
    • Picocell
    • Microcell
    • Macrocell

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Architecture

  • It defines the order or the hierarchy in the wireless devices/terminals
  • Wireless link access depends on the network architecture
  • Objective of network design determine the network architecture
  • Network architecture can be classified as centralized, distributed and hybrid
  • Centralized networks have fixed infrastructure and central controller
  • Distributed networks do not have fixed infrastructure or central controller

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Centralized architecture

    • Examples: Cellular networks, WiMAX, Bluetooth (master-slave) etc.
    • Consists of a base station/central controller who schedules/allocates resources to the wireless hosts
    • Base station implements a scheduling algorithm
    • Typically follow multiple access schemes
    • Multichannel resource allocation is followed
      • Contiguous or discontiguous chunks of bandwidth
    • QoS support guaranteed: Throughput; fairness; load balancing; delay guarantees

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Distributed architecture

    • Examples: Wireless LANs, Wireless sensor networks, ad hoc networks, Bluetooth (peer-peer), etc.
    • Require MAC protocols for coordination
    • Wireless hosts compete for resources using random access techniques
    • Multichannel access is difficult to implement
    • QoS support not guaranteed
    • Scalability and fairness are not an issue
    • Fewer control overhead compared to centralized architecture

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Hybrid architecture

    • Examples: 5G networks, Cooperative networks, MANETs, VANETs, etc.
    • Combination of centralized and distributed network architectures
    • Requires a combination of protocols and algorithms
    • Coexistence of different networks should be guaranteed
    • No unique architecture exists
    • QoS support: Latency; fairness; throughput; scalability

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Comparison

Centralized architecture

Distributed architecture

Hybrid architecture

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Standards

  • Wireless standards are defined by IEEE, IETF, ETSI, IEC, etc.
  • Standards usually specify the PHY and MAC
    • In some cases, they may specify the upper layers
  • Some IEEE Standards are given below:
    • IEEE 802.11
    • IEEE 802.15
    • IEEE 802.16
    • IEEE 802.3
    • IEEE 1900

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Wireless Network Architectures and Standards

SELECTED TOPICS IN NETWORK DESIGN

Wireless networks – Standards

  • Some 3GPP/ETSI standards include
    • GSM
    • cdma2000
    • UMTS
    • E-UTRA
    • DECT
  • Some IEC standards
    • IEC 61850
    • IEC 62645

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Selected Topics in Network Design

Wireless Network Design Requirements – Part I

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Network Design – Part I

SELECTED TOPICS IN NETWORK DESIGN

Network design – Basics

  • Network design deals with identifying a suitable network architecture to satisfy a given design objective
  • Network design also involves defining the characteristics of the network when it becomes operational
  • Typical operational characteristics
    • Link access
    • Frame structure
    • Overheads
    • Power consumption
    • Achievable data rates
  • Network design is motivated by the application and the number of end-users to be supported

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Wireless Network Design – Part I

SELECTED TOPICS IN NETWORK DESIGN

Network design – Basics (contd.)

  • Typically, network can be viewed as a set of nodes partially or fully connected by links
  • Networks composed of terminal nodes and resource nodes
  • Terminal nodes run application which generates packets
  • Resource nodes provide connectivity and other services
  • Network design issues in centralized or distributed cases are very different

Internet

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Wireless Network Design – Part I

SELECTED TOPICS IN NETWORK DESIGN

Wireless network design requirements

    • Define the roles of the nodes
    • Define the interaction between the nodes
    • Define the data required for the network design
    • Define the notations/symbols to be used
    • Define the objective of the network design
    • Define mathematical model for the network design
    • Define an algorithm for optimizing the objective
    • Define criteria for analyzing the network design

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Wireless Network Design – Part I

SELECTED TOPICS IN NETWORK DESIGN

Defining the roles of the nodes

    • Terminal nodes and resource nodes have different roles in different network architectures
      • In centralized network architecture, resource nodes are hubs, base stations or access points
      • In distributed networks, the resource nodes could be the same as the terminal nodes
    • Resource nodes generally collect information from terminal nodes or other resource nodes
    • Resource nodes act as relays and/or schedulers
    • Terminal nodes send and receive data

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Wireless Network Design – Part I

SELECTED TOPICS IN NETWORK DESIGN

Defining the roles of the nodes (contd.)

    • Roles should be defined in the hierarchy

A. Checko et al., "Cloud RAN for Mobile Networks – A Technology Overview,“ IEEE Commun. Surv., vol. 17, no. 1, pp. 405-426, First quarter 2015

C–RAN (5G)

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Selected Topics in Network Design

Wireless Network Design Requirements – Part II

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

147 of 553

Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Defining the interaction between the nodes

  • Nodes interact based on the network architecture using frames
  • A frame is a timeline for exchange of control information and data between pairs (or groups) of nodes
    • Frame facilitates coordination between the nodes
  • In centralized network architecture, the frame is defined and periodically scheduled by the central controller
    • Here, frame is meant for coordination of all nodes
    • Scheduling algorithm determines the status and the meaning of the information within a frame
    • Central controller specifies the duration and schedule for data transmissions

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Defining the interaction between the nodes (contd.)

  • In the distributed architecture, frames are meant for coordination between sender and receiver
    • Here, frame is scheduled randomly and may suffer from interference (i.e., collision)
    • Frame comprises of synchronization bits, sender and receiver identity, header for the data and the data
    • Different types of frames are deployed for different purposes
    • Examples: RIP messages in ad hoc networks, IEEE 802.11 frame under DCF with RTS/CTS

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Defining the interaction between the nodes (contd.)

  • In multihop communication, relay nodes play an important role

Internet

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

  • First, the network architecture is described and then the interaction is described

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

  • An 802.16 wireless service provides a communications path between a subscriber site and the core network

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

    • Referred to as IEEE 802.16
    • For more information http://www.wimaxforum.org/
    • WiMAX operates in both licensed (2.5 GHz and 3.5 GHz) and unlicensed bands (2.4 GHz and 5 GHz).
    • IEEE 802.16e PHY is based on OFDMA with TDD or FDD
  • Both uplink and downlink transmissions are scheduled by the WiMAX base station
    • Uplink means transmissions from mobile users to base station
    • Downlink means transmissions from base station to mobile users

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

  • The frame size and allocations are determined by the scheduler
  • The scheduler is located at the base station
  • The channel conditions are obtained from every terminal over the CQICH
  • For DL, using the QoS of each service flow and the channel conditions, the correct modulation and coding are selected
  • For UL, the bandwidth requests and QoS requirement of each service flow are collected on the UL ranging
  • The best subcarriers per service flow are mapped and broadcast in the UL MAP and DL MAP

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Wireless Network Design – Part II

SELECTED TOPICS IN NETWORK DESIGN

Case study of node interaction: Centralized (WiMAX)

  • Other operations managed by the base station
    • Handoff
    • Power management
    • Security

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Selected Topics in Network Design

Wireless Network Design Requirements – Part III

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

  • Network design requires data (information) about terminal nodes, resource nodes and wireless links
  • The data can be local or global
  • The data can be constants or random variables
  • If the data is comprised of random variables, then it must be generated
  • Time of occurrence of data and the process of data sharing must be specified

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of large scale fading

      • First two terms on the RHS are constants
      • For third term, generate Gaussian random variables

, here is between 8-13 dB

      • The channel gain can be expressed as

y[n] = g[n] s[n] + x[n]

where x[n] is AWGN, s[n] is transmitted signal and g[n] is path loss

      • Note, for discrete samples we can replace t by n

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of large scale fading with temporal correlation
      • Suppose the correlation decays over m samples by a factor β

      • Here, v[n] and d[n] are velocity and distance in the n-th slot, and 0 < εD < 1
      • Thus, the n-th sample of the received signal can be expressed as y[n] = a y[n-1] + x[n]

where x[n] is AWGN and

where

and

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of small scale fading
      • Impulse response of the channel is expressed as

h[n] = an ej𝜃n𝛿[n]

      • The phase θn follows uniform distribution [0,2π]
          • In MATLAB, use function rand and adjust for variance
          • In Python, use numpy.random.rand and adjust for variance
        • For amplitude an we can generate according to the presence or absence of the LOS

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of small scale fading (contd.)
      • For the case with no LOS, an follows Rayleigh distribution

      • Draw two Gaussian random variables u and v with mean zero and variance 𝜎2
      • Then, the random variable an is given by (u2 + v2)0.5

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of small scale fading (contd.)
      • For the case with strong LOS, an follows Rice distribution

      • The mean and variance are given by

Modified Bessel function of order zero

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of small scale fading (contd.)
    • Draw two independent Gaussian RVs u ~ N(μcosθ, σ2) and v ~ N(μsinθ, σ2)
    • The Rice distributed random variable an is given by

(u2 + v2)0.5

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of packet events
    • Packet arrivals generally are assumed to follow Poisson process or Bernoulli process
    • Poisson process can be generated as follows:
      1. Generate exponential random number (e.g., y=numpy.random.exponential (1/a))
      2. If no. of arrivals = 0 then store x[0] = y
      3. If no. of arrivals is >0 then store x[n] = x[n-1] + y
      4. Go to step 1

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of packet events
    • For any general distribution, we use the Monte Carlo method to generate the random process
    • Let x1,...,xm denote the random variables occurring with probabilities p1,...,pm respectively
      1. Generate uniform random number U

(e.g., U=numpy.random.uniform() in Python)

      • Set X = xj if

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the decisions for network design

    • Decisions refer to the unknowns which have to be found to satisfy the design objective(s)
      • Examples: Assignment of spectrum blocks to end-users; Transmit power assigned to downlink channel; Flow rate across a link
    • Decisions and data are combined to express the constraints in the mathematical model
      • Examples of constraints: SINR calculated through transmit power should be above minimum SINR target

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the decisions for network design (contd.)

    • Decisions can also be local or global
    • The order of occurrence of the data and decisions must be specified
    • The time scale over which the decisions are taken must be specified
      • Example:
        • Consider a static multihop wireless network in which the wireless terminals want to exchange data with one another. What will be the data, decisions and order of occurrence? Which data is local or global? Which decision is local or global?

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the notations/symbols

    • Data is specified in uppercase
    • Decisions are specified in lowercase
      • Single letter or symbol is preferred for notation
    • Indexes are given in subscripts while labels (e.g., min) are given in superscript
    • Vectors and matrices are expressed in boldface
    • Examples of notations:
        • Flow rate across a link (i,j) can be denoted as fij
        • Minimum bit rate required by receiver j can be denoted as Rjmin

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Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the notations/symbols (contd.)

    • Sets for the indexes can be specified in uppercase stylized fonts

    • Size of such a set can be denoted as

    • Functions are also given subscripts or superscripts according to their dependent parameters

    • Examples of notations to be avoided

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Selected Topics in Network Design

Wireless Network Design Requirements – Part III

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

172 of 553

Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

  • Network design requires data (information) about terminal nodes, resource nodes and wireless links
  • The data can be local or global
  • The data can be constants or random variables
  • If the data is comprised of random variables, then it must be generated
  • Time of occurrence of data and the process of data sharing must be specified

173 of 553

Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of large scale fading

      • First two terms on the RHS are constants
      • For third term, generate Gaussian random variables

, here is between 8-13 dB

      • The n-th sample of the received signal can be expressed as

y[n] = g[n] s[n] + x[n]

where x[n] is AWGN, s[n] is transmitted signal and g[n] is path loss

174 of 553

Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of large scale fading with temporal correlation
      • Suppose the correlation decays over m samples by a factor β

      • Here, v[n] and d[n] are velocity and distance in the n-th slot, and 0 < εD < 1
      • Thus, the n-th sample of the received signal can be expressed as y[n] = a y[n-1] + x[n]

where x[n] is AWGN and

where

and

175 of 553

Wireless Network Design – Part III

SELECTED TOPICS IN NETWORK DESIGN

Defining the data for network design

    • Simulation of small scale fading
      • Impulse response of the channel is expressed as

h[n] = an ej𝜃n𝛿[n]

      • The phase θn follows uniform distribution [0,2π]
          • In MATLAB, use function rand and adjust for variance
          • In Python, use numpy.random.rand and adjust for variance
        • For amplitude an we can generate according to the presence or absence of the LOS

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Defining the data for network design

    • Simulation of small scale fading (contd.)
      • For the case with no LOS, an follows Rayleigh distribution

      • Draw two Gaussian random variables u and v with mean zero and variance 𝜎2
      • Then, the random variable an is given by (u2 + v2)0.5

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Wireless Network Design – Part III

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Defining the data for network design

    • Simulation of small scale fading (contd.)
      • For the case with strong LOS, an follows Rice distribution

      • The mean and variance are given by

Modified Bessel function of order zero

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Wireless Network Design – Part III

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Defining the data for network design

    • Simulation of small scale fading (contd.)
    • Draw two independent Gaussian RVs u ~ N(μcosθ, σ2) and v ~ N(μsinθ, σ2)
    • The Rice distributed random variable an is given by

(u2 + v2)0.5

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Wireless Network Design – Part III

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Defining the data for network design

    • Simulation of packet events
    • Packet arrivals generally are assumed to follow Poisson process or Bernoulli process
    • Poisson process can be generated as follows:
      1. Generate exponential random number (e.g., y=numpy.random.exponential (1/a))
      2. If no. of arrivals = 0 then store x[0] = y
      3. If no. of arrivals is >0 then store x[n] = x[n-1] + y
      4. Go to step 1

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Defining the data for network design

    • Simulation of packet events
    • For any general distribution, we use the Monte Carlo method to generate the random process
    • Let x1,...,xm denote the random variables occurring with probabilities p1,...,pm respectively
      1. Generate uniform random number U

(e.g., U=numpy.random.uniform() in Python)

      • Set X = xj if

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Wireless Network Design – Part III

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Defining the decisions for network design

    • Decisions refer to the unknowns which have to be found to satisfy the design objective(s)
      • Examples: Assignment of spectrum blocks to end-users; Transmit power assigned to downlink channel; Flow rate across a link
    • Decisions and data are combined to express the constraints in the mathematical model
      • Examples of constraints: SINR calculated through transmit power should be above minimum SINR target

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Wireless Network Design – Part III

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Defining the decisions for network design (contd.)

    • Decisions can also be local or global
    • The order of occurrence of the data and decisions must be specified
    • The time scale over which the decisions are taken must be specified

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Defining the notations/symbols

    • Data is specified in uppercase
    • Decisions are specified in lowercase
      • Single letter or symbol is preferred for notation
    • Indexes are given in subscripts while labels (e.g., min) are given in superscript
    • Vectors and matrices are expressed in boldface
    • Examples of notations:
        • Flow rate across a link (i,j) can be denoted as fij
        • Minimum bit rate required by receiver j can be denoted as Rjmin

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Defining the notations/symbols (contd.)

    • Sets for the indexes can be specified in uppercase stylized fonts

    • Size of such a set can be denoted as

    • Functions are also given subscripts or superscripts according to their dependent parameters

    • Examples of notations to be avoided

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Selected Topics in Network Design

Wireless Network Design Requirements – Part IV

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Network Design – Part IV

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Defining the objective of the network design

    • The goal of network is to achieve the desired objective in terms of the decisions
    • Objectives can be defined from standpoint of end-users or network operator or application
    • Objectives also depend on the network architecture
    • Examples of objectives
      • Maximize sum data rate of all links
      • Maximize energy efficiency
      • Minimize the system delay
      • Minimize operating costs
      • Minimize capital costs and expected operating costs
      • Maximize revenue of network operator

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Wireless Network Design – Part IV

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Defining the objective of the network design

  • Mathematically, the objective is referred to as objective function
  • The objective function returns a scalar value with respect to the decisions
  • The best value of the decisions is called optimal solution and the best value of the objective function is called optimal value

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Wireless Network Design – Part IV

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Defining the objective of the network design

  • Example of objective function
    • Let (i,j) denote a pair of nodes (i.e., link) in the network
    • Let the links share the spectrum blocks of bandwidth Bj
    • Let the transmit power on link (i,j) be denoted as pi
    • The power received by node j is piGij where Gij is channel gain of link (i,j)
  • State the objective function as maximizing sum data rate across all links

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Wireless Network Design – Part IV

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Defining the mathematical model for network design

  • We define the a set of rules/equations that relate the data and the decisions which are referred to as constraints
  • Combining the objective function and the constraints makes the network design problem mathematical
  • The best decisions are found by solving the mathematical model using iterative algorithms
  • These algorithms can be either based on the optimization techniques or heuristic algorithms

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Wireless Network Design – Part IV

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Defining the mathematical model for network design

  • Case study – Orthogonal link access in centralized network architecture:
    • Let m denote the index of the base station
    • Let i {1,..,N} denote the terminal nodes which await transmissions from the base station
    • Consider downlink scheduling by the base station using the frequency channels k{1,..,K}

Gmik

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Wireless Network Design – Part IV

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Defining the mathematical model for network design

  • Case study – Orthogonal link access in centralized network architecture:
    • Let Gmik denote the path loss (channel gain) estimated by the terminal node i on the channel k
    • Let Bk denote the bandwidth of each channel k
    • Let N0 denote the noise power density
    • Let I denote the inter-cell interference
    • Let Pmax denote the maximum transmit power of the base station

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Wireless Network Design – Part IV

SELECTED TOPICS IN NETWORK DESIGN

Defining the mathematical model for network design

  • Case study – Orthogonal link access in centralized network architecture:
    • Let pmik denote the transmit power from base station to node i on the channel k
    • Let aik denote the assignment of downlink transmission on channel k to node i
    • Consider the objective is to maximize the sum data rate of all assigned wireless links

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Wireless Network Design – Part IV

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Defining the mathematical model for network design

  • Case study – Orthogonal link access in centralized network architecture:
    • Constraint 1: Each terminal node i must be assigned a unique channel

    • Constraint 2: Minimum rata rate requirement must be met for each terminal node

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Wireless Network Design – Part IV

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Defining the mathematical model for network design

  • Case study – Orthogonal link access in centralized network architecture:
    • Constraint 3: Base station should not transmit beyond the maximum available power

    • Constraint 4: Transmission allowed only on assigned links

    • Constraint 5: Integrality condition

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Selected Topics in Network Design

Wireless Network Design Requirements – Part V

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless Network Design – Part V

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Modeling – Shared resource allocation

    • Consider a heterogeneous cell where same bandwidth-time slots (i.e., channels) are shared across multiple cells
    • Within each cell (femto or macro), the channels are orthogonally assigned
    • Consider scheduling of downlink transmissions in all cells
    • Consider M femtocells, so m ∈ {1,...,M} where m is index of femto base station (BS)
    • Each femto BS talks to one femto user m’ ∈ Um
    • Let n and n’ ∈ {1,...,N}\n denote the macro BS and the macro users respectively
    • Let k ∈ {1,...,K} denote the channel index

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Let In’, and Im’ denote the interference thresholds of the receivers n’ and m’
    • Let Gmm’k and Gnn’k denote the channel gain measured by receiver m’ and n’ with respect to m (femto BS) and n (macro BS)

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Let Gnm’k and Gmn’k denote the channel gain measured by receiver m’ and n’ due to interference from n and m respectively
    • Interference between femto cells is negligible as they are non-overlapping

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Let Pm and Pn denote the maximum transmit powers of femto BS m and macro BS n
    • Let pmm’k and pnn’k denote the transmit powers from femto BS and macro BS to respective receivers m’ and n’ on channel k
    • Let an’k denote the binary variable to orthogonally assign channel k ∈ {1,...,K} to respective macro cell users

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Implement of shared resource allocation depends on network architecture
    • Centralized architecture: A central controller collects information from both types of cells (via the BSs) and broadcast the decisions
    • Distributed architecture:
      • Femto BSs determine decisions locally and broadcast their results to macro BS
      • Macro BS determines its decisions and broadcasts its results to all femto BSs
      • The above steps repeat as data rates are maximized while the interference conditions are not violated

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Modeling – Shared resource allocation (Soln.)

    • Centralized architecture:

    • TDM/OFDM slots for control and data messages
    • Distributed architecture:

    • Femto BS and macro BS can transmit control messages in iterative manner or pseudorandom manner

Uplink control messages

Scheduling

Downlink control messages

Data transmission phase

Data transmission phase

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • The objective is to maximize the sum data rate of all transmissions in the heterogeneous cell

Here, pnm’k is same for all femto users . It is given by

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Constraint 1: Interference experienced by femto user m’ must not exceed the corresponding interference threshold

    • Constraint 2: Interference experienced by macro user n’ must not exceed the corresponding interference threshold

    • Constraint 3: Orthogonal assignment of channels for macro cell users

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Wireless Network Design – Part V

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Modeling – Shared resource allocation (Soln.)

    • Constraint 4: Total transmit power constraint for femto BS

    • Constraint 5: Total transmit power constraint for macro BS

    • Constraint 6: Transmit power assignment per channel for macro BS and femto BS

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Wireless Network Design – Part V

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Defining criteria for analyzing network design

    • Network designs can be analyzed using experiments
      • Each experimental run involves fresh dataset
    • Analysis allows the decision maker to modify the design
    • Analysis allows the decision maker to understand limitations of the network design
    • Analysis reveals scalability, computation complexity and accuracy of the decisions
    • Markov chains have been extensively applied to analyze network designs
    • Optimization techniques have also been expensively applied to analyze network designs

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Wireless Network Design – Part V

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Analysis –Shared resource allocation

  • Best objective (sum data rates) can be analyzed by varying
    • No. of channels K
    • No. of femto cells M
    • Interference threshold In’ or Im’
    • Variance of the channel gains
    • No. of active macro cell users N
  • Stability of the design (e.g., outage events, congestion)
  • Analyze the convergence time and tradeoffs
  • Analyze impact of overheads and link rates

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Selected Topics in Network Design

Markov Chains – Basics and Applications

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Markov chains – Basics and applications

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Introduction

    • When the best decisions are taken by scheduling problems (i.e., link access problems) the resources are best utilized
    • It is important to know whether, the available resources are sufficient
    • Packet arrivals, bandwidth requests, link rates, nodal processing delays, handoffs, etc. are random in nature
    • Hence, stability of the system and resource utilization are of prime importance in network design
    • In other words, we must determine the performance of the system under random events

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Markov chains – Basics and applications

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Introduction (contd.)

    • Markov chains represent the evolution of the available resources in the network due to the decisions
      • Examples:
      • Evolution of busy bandwidth-time slots (i.e., channels) due to random requests
      • Evolution of nodal processing rate due to random packet arrivals
    • More specifically, the Markov chains represent evolution of random processes which have the following properties
      • Orderliness
      • Independence
      • Stationarity

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Markov chains – Basics and applications

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Introduction (contd.)

    • Examples of random process modelled as Markov chains include Poisson process, Bernoulli process, etc.
    • Markov chains are said to follow Markov property (aka memoryless property)
    • Packet arrivals or bandwidth/service requests in wireless networks generally follow memoryless property
    • Markov chains (MC) are used to study performance of scheduling policy/mathematical model/protocols
    • The following analysis can be performed using MC
      • Throughput analysis
      • Delay analysis
      • Outage analysis

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Markov chains – Basics and applications

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Introduction (contd.)

    • Other applications of Markov chains
      • Telecommunication network design
      • Systems scheduling and control
      • Highway design
      • City planning
      • Hospital management
      • Airport design
      • Reliability engineering

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Markov chains – Basics and applications

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Markov chains – Math representation

    • Markov chains are represented as follows
      • Set of finite states (S)
      • Transition rates (Q) / Transition probabilities (P)
      • Stationary probability distribution of the states (π)
    • Types of Markov chains
      • Discrete time Markov chain (DTMC) – Meant for describing discrete time random process
      • Examples: Centralized networks with synchronous requests
      • Continuous time Markov chains (CTMC) – Meant for describing continuous time random process
      • Examples: Distributed networks with synchronous or asynchronous requests

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Markov chains – Basics and applications

SELECTED TOPICS IN NETWORK DESIGN

Markov chains – Math representation – DTMC

    • Let S0, S1, ..., Sn, Sn+1,... denote a memoryless random process occurring at discrete time instants 0,1,...,n,n+1,...

    • The Markov property or memoryless property is given by

P(Sn+1 | Sn,..., S0) = P(Sn+1 | Sn) = P(S1 | S0)

    • P(Sn+1 | Sn) is referred to as transition probability

    • Suppose the set of states is given by 𝒮 = {s1,s2,...,sN} then we can define an N × N transition probability matrix P

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Markov chains – Math representation – DTMC (contd.)

    • A realization of the random process is obtained by choosing an initial state S0 = s1 and choosing the next state randomly based on the transition probabilities

P(S1 = sj | S0 = s1) or P(Sn+1| Sn = s1) with n = 0

      • Use Monte Carlo method
    • Next, we increment n and choose new state based on P

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC (contd.)

    • Choose the next state randomly based on the transition probabilities

P(Sn+1 = sk | Sn = sj) where j = 1,...,N and k = 1,...,N

    • Increment n and repeat above step

Some observations:

    • Note that all state transitions may not be possible
    • When every state can be visited from every other state then we call the Markov chain as irreducible
    • We can calculate the mean recurrence time for different states in an irreducible Markov chain

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC (contd.)

    • In order to find the steady state distribution (π), define the initial distribution π0 = [π1,0, π2,0,..., πN,0]
    • Here, the state probability πj,n = P(Sn = sj) where j = 1,...,N
    • The state probability in the next state (i.e., in step n+1) is given by

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC (contd.)

    • The steady state probability (π) can be written as

    • Normalization equation :

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • According to Kemeny et al.1, the Land of Oz is blessed by many things, but not by good weather. They never have two nice days in a row. If they have a nice day, they are just as likely to have snow as rain the next day. If they have snow or rain, they have an even chance of having the same the next day. If there is change from snow or rain, only half of the time is this a change to a nice day.
      • Find the steady state distribution
      • Given that today is a nice day, what is the probability that the 4th day will be rainy?

      • J. G. Kemeny, J. L. Snell, G. L. Thompson, Introduction to Finite Mathematics, 3rd ed. (Englewood Cliffs, NJ: Prentice-Hall, 1974).

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • Let the set of states be defined as 𝒮 = {sR, sN, sS}
    • Step 1: Finding transition probability matrix
    • They never have two nice days in a row.

P(Sn+1 = N|Sn = N) = 0

    • If they have a nice day, they are just as likely to have snow as rain the next day.

P(Sn+1 = S|Sn = N) = P(Sn+1 = R|Sn = N)

P(Sn+1 = N|Sn = N) + P(Sn+1 = R|Sn = N) + P(Sn+1 = S|Sn = N) = 1

🡪 P(Sn+1 = S|Sn = N) = P(Sn+1 = R|Sn = N) = 0.5

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • If they have snow or rain, they have an even chance of having the same the next day.

P(Sn+1 = S|Sn = S) + P(Sn+1 = R or N|Sn = S) = 1

🡪 P(Sn+1 = S|Sn = S) = 0.5

P(Sn+1 = R|Sn = R) +P(Sn+1 = S or N|Sn = R) = 1

    • P(Sn+1 = R|Sn = R) = 0.5

    • If there is change from snow or rain, only half of the time is this a change to a nice day.

P(Sn+1 = N|Sn = S) = 0.25 (i.e., half of 0.5)

P(Sn+1 = N|Sn = R) = 0.25 (i.e., half of 0.5)

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • So P(Sn+1 = R|Sn = S) = 0.25 and P(Sn+1 = S|Sn = R) = 0.25

    • Then P is defined as 3 × 3 transition probability matrix

    • Let initial distribution be denoted as π0 = [πR,0, πN,0, πS,0]
    • Assume some arbitrary values for πj,0 where j {R,N,S} while normalization condition is satisfied
    • Say, π0 = [0, 1, 0]

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • Steady state is given by repeating πn+1 = Pπn where n = 0,1,...

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Markov chains – Basics and applications

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Markov chains – Math representation – DTMC Example

    • Convergence happens by 8th iteration to give

π = [0.4, 0.2, 0.4]

    • Given day 0 is nice, P(4th day being rainy) = πR,3 = 0.40625

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Selected Topics in Network Design

Markov Chains – Applications to Queuing Theory

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Markov Chains – Applications to Queuing Theory

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Introduction

    • Network design can be viewed as management of interconnected queues
    • Queue status in the nodes vary with arrivals and departure of packets/requests
      • Arrival events and resource availability can be random
      • Link access methods determine the departure events
    • Mismanagement of queues leads to congestion and loss of packets/requests (i.e., outage events)
    • Hence, study of queues (aka queuing theory) becomes very important
    • Markov chains have been extensively applied to queuing theory

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Markov Chains – Applications to Queuing Theory

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Basics of queuing theory

    • Queues in a network are managed either by increasing the resources or redirecting the packets/requests elsewhere
    • Let’s visualize a single node in a wireless/wired network as a queuing model

Buffer (queue status)

Arrival Process

Departure Process

Service rate (resource based)

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Markov Chains – Applications to Queuing Theory

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Basics of queuing theory (contd.)

    • In order to visualize the node as Markovian model the arrivals and/or departures must be memoryless
    • The queue status can be treated as the state of the MC
    • The state transition probability matrix P must be defined
    • The steady state distribution of the queue must be found
    • Using the steady state distribution we can find
      • Mean queue size
      • Throughput of the node

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Markov Chains – Applications to Queuing Theory

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Basics of queuing theory

    • Similar to single node queuing model, we also have multi-server queuing models

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Markov Chains – Applications to Queuing Theory

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DTMC example: Queuing model

    • Suppose a resource node is storing and forwarding packets according to the probability distributions given below.

Suppose the total buffer size (B) is 3 packets.

    • Find the mean number of packets in the buffer.
    • Find the probability of dropping the packets.

# arrival

0

1

2

3

P(#arrival)

0.1

0.4

0.2

0.3

# departure

0

1

2

P(#departure)

0.25

0.5

0.25

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Markov Chains – Applications to Queuing Theory

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DTMC example: Queuing model (contd.)

    • Let qn denote the state (queue status) of the MC
    • So qn {0,...,B} where B = 3 packets and n = 0,1,2,...
    • The state evolves with arrivals and departures in n

    • Assume departures occur first followed by arrivals
    • So the transition probabilities are given by

    • Note that an = i based on P(an = i) where i {0,...,3}
    • Similarly dn depends on qn and the departure process

qn+1 = qn – dn + an

P(qn+1 = k’|qn = k) where k, k’ {0,...,B}

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Markov Chains – Applications to Queuing Theory

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DTMC example: Queuing model (contd.)

    • dn = min(qn, j) = min(k, j) where k {0,...,B} and j {0,1,2}

which occurs with P(#departure = j)

    • Therefore, qn+1 = k’ can be expressed as

    • As k’ {0,...,B}, we rewrite the transition function as

    • So the transition probabilities are given by

k’ = k – min(k, j) + i

k’ = min(B, max(k – min(k, j) + i, 0))

P(qn+1 = k’|qn = k) =

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Markov Chains – Applications to Queuing Theory

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DTMC example: Queuing model (contd.)

  • Size of transition probability matrix P is (B+1) × (B+1)
  • Apply the recursive formula πn+1 = n for n = 0,1,....
    • Here, πn = [π0,n ,...., πB,n] where πk,n = P(qn = k)
  • The steady state probability is given by π
  • Mean queue size and blocking probability are given by

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Markov Chains – Applications to Queuing Theory

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DTMC example: Queuing model (contd.)

  • Numerical values

Pk’|k

k=0

k=1

k=2

k=3

k’=0

0.1

0.075

0.025

0

k’=1

0.4

0.325

0.15

0.025

k’=2

0.2

0.25

0.275

0.15

k’=3

0.3

0.35

0.55

0.825

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Markov Chains – Applications to Queuing Theory

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Markov chains – Some notations

Symbol

Description

λ

Mean arrival rate

μ

Mean service rate

a

Traffic intensity

ρ

Traffic utilization

E[D]

Mean system delay

E[Q]

Mean number of packets in the system

E[W]

Mean queuing delay

E[NQ]

Mean number of packets waiting in the queue

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Markov Chains – Applications to Queuing Theory

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Markov chains – Some important definitions

  • Consider system having multiple servers m
  • System utilization: Ratio of time a server is busy to the time it is available

  • Traffic Intensity: Product of mean arrival rate and the mean service time

    • Little’s theorem: Mean queue size equals the product of mean arrival rate and mean waiting time

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Markov Chains – Applications to Queuing Theory

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Markov chains – Some important definitions

    • Flow conservation principle: For a lossless system what goes into the system is equal to what comes out of the system

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Markov Chains – Applications to Queuing Theory

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Markov chains – Example

    • For the example derive the relation between all arrival rates using the flow conservation principle
    • Derive the utilization for each server

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Markov Chains – Applications to Queuing Theory

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Markov chains – Example (contd.)

    • At CPU, we have incoming and outgoing rate as
    • As some packets are diverted to the disk with probability P we have λDISK = P λCPU
    • The incoming rate and outgoing rate of the entire system is λ, we have λ = (1-P) λCPU
    • By flow conservation we have λDISK = λ + λCPU
    • The utilization of resources are given by

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Selected Topics in Network Design

Markov Chains – CTMC

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Markov Chains – CTMC

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CTMC – Math representation

    • Suppose the set of states is given by 𝒮 = {s1,s2,...,sN}
    • Suppose, a random process {Xt} taking random values from 𝒮 for t > 0
    • The Markov property can be stated as

    • Suppose a state Xt = i occurs. Then S–1 random timers are chosen based on the their respective exponential distributions with mean 1/Qij where j 𝒮\i
    • Once a timer expires, the state Xt+s occurs taking the corresponding value from 𝒮

where s, t ≥ 0 and 0 ≤ v<s

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Markov Chains – CTMC

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CTMC – Math representation

    • The transition rate Qii is given by

    • Based on the flow conservation principle, we can state that the expected transitions into a state i is equal to the expected transitions out of state i
    • Alternatively, we can state that the total probability flux entering state i is equal to total probability flux leaving state i
      • Probability flux is given by product of state probability and its associated transition rates

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Markov Chains – CTMC

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CTMC – Math representation

    • Rearranging the equations gives rise to the global balance equations

    • In matrix form, we can express the above equations as

    • Here, Q is the referred to as infinitesimal generator matrix and π is called the steady state distribution

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CTMC – Queuing model example

    • Consider an edge server receiving requests from IoT devices over an ideal wireless channel. Suppose every request is served without being blocked. Suppose the arrival of requests to the server follows Poisson distribution with mean arrival rate of λ = 4 jobs/sec and the service times follow exponential distribution with mean service rate of μ = 5 jobs/sec.
    • Find steady state distribution (π)
    • Find mean queue size
    • Find the mean waiting time for a job in the system

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Markov Chains – CTMC

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CTMC – Queuing model example (Soln.)

    • The given example is referred to as M/M/1/ model
    • This model has an infinite capacity for arrivals to wait before service if the server is busy
    • The state of the edge server can be described by the number of requests in the system (i.e., currently in service plus those waiting). Let k denote the state

Service facility

Waiting workloads

Arrival

Departure

Server

Workload

being processed

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Markov Chains – CTMC

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CTMC – Queuing model example (Soln.)

    • The state transitions can be depicted as

    • The global balance equations for the above transitions can be written using state k

k+1

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CTMC – Queuing model example (Soln.)

    • This results in an infinite number of global balance equations which can be solved using z-transform
    • Alternatively, for such Markov chains, we can apply local balance method
      • Local balance method requires only two states at a time
    • Using state 0 and 1, we get

    • Using state 1 and 2, we get

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CTMC – Queuing model example (Soln.)

    • By induction, we get

    • Using the normalization condition, we get

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Markov Chains – CTMC

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CTMC – Queuing model example (Soln.)

    • Mean occupancy of the edge server can be calculated as

    • Using the Little’s theorem, we get mean delay for any request

    • Deriving mean queuing delay E[W]

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Markov Chains – CTMC

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CTMC – Queuing model example (Soln.)

    • Mean queue size (i.e., mean requests waiting to be served)

    • Numerical values:

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Markov Chains – CTMC

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CTMC – Other queuing models in network design

    • Single server model with finite buffer
      • Resource nodes such as routers, access points, relays and terminal nodes having single processor
    • Multi-server model with finite buffer
      • Scheduling problems by 4G cellular base station
      • Coordinated transmission in C-RAN using multiple RRHs
    • Multi-server model with no buffer
      • 3G cellular base stations performing voice calls
      • Maintenance scheduling problems
      • Service center operation

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Selected Topics in Network Design

Markov Chains – Numerical examples

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Markov chains – Numerical examples

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Example 1:

    • Variable-length data packets arrive at a communication node according to a Poisson process with an average rate of 180 packets per minute. The single outgoing link is operating at a transmission rate of 4800 bps. The packet length can be assumed to be exponentially distributed with an average length of 120 characters in 8 (7+1) ASCII format.
    • Analyze the performance of this communication link assuming that it has a very large buffer.
    • What is the probability that 7 or more packets are waiting to be transmitted?

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Example 1: Solution

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Markov chains – Numerical examples

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Example 2:

  • Suppose a packet switch accepts two types of packets: voice packets (mean arrival rate is λ1) and data packets (mean arrival rate is λ2). Suppose the switch spends the same time for servicing (mean rate μ). Suppose the data packets are allowed only when the total packets in queue is less than or equal to N. Assume arrivals follow Poison distribution and departure times are exponentially distributed.
    • Derive the queue distribution for the case where the buffer size is infinite.

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Example 2: Solution

    • The state transition diagram is given below

    • Apply local balance concept for k N

    • Let ρ = (λ1+ λ2)/μ so

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Markov chains – Numerical examples

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Example 2: Solution (contd.)

    • The state transition diagram is given below

    • By induction for k N

    • Apply local balance concept for k > N

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Example 2: Solution (contd.)

    • The state transition diagram is given below

    • Let ρ1 = λ1 so

    • By induction for k > N

N

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Example 2: Solution (contd.)

    • Given and

    • Find π0 using normalization condition

N

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Markov chains – Numerical examples

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Example 2: Solution (contd.)

    • Thus the queue distribution is given by

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Markov chains – Numerical examples

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Example 3:

    • Suppose a packet switch accepts two types of packets: voice packets (mean arrival rate is λ1) and data packets (mean arrival rate is λ2). Suppose the switch spends the same time for servicing (mean rate μ). Suppose the data packets are allowed only when the total packets in queue is less than or equal to N. Assume arrivals follow Poison distribution and departure times are exponentially distributed.
    • Derive the queue distribution for the case where the buffer size is finite B which is greater than N.

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Example 3: Solution

    • Calculation is similar to previous example except for the condition that the states are finite (ends at B >N)

    • To find the π0

N

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Example 3: Solution

    • Thus the queue distribution can be expressed as

N

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Selected Topics in Network Design

Basics of Optimization

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Basic Concepts

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Fundamentals of optimization

Subject to:

Objective function

Constraints

Decision variables

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Basics of Optimization

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Fundamentals of optimization

    • Types of problems by structure: Unconstrained optimization, linear program, integer programs, convex programs, non-linear programs, multi-objective problems, etc.
    • Types of problems by uncertainty: Deterministic problems and stochastic problems
    • Types of stochastic problems: single stage problems, two stage/multi-stage problems, robust problems, chance-constrained problems, risk-averse problems, etc.

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Basics of Optimization

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Solving optimization problems

    • Solved iteratively by evaluating a sequence of feasible solutions
    • Start with a feasible solution and evaluate the function
    • Determine a new search direction (e.g., based on gradient of f0(x))
    • Determine the optimal step length
    • Update the feasible solution using steps 3 and 4
    • Repeat the above steps till the stopping criteria is satisfied

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Basics of Optimization

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Solving optimization problems

    • Solved iteratively by evaluating a sequence of feasible solutions
    • Start with a feasible solution and evaluate the function
    • Determine a new search direction (e.g., based on gradient of f0(x))
    • Determine the optimal step length
    • Update the feasible solution using steps 3 and 4
    • Repeat the above steps till the stopping criteria is satisfied

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Basics of Optimization

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Unconstrained optimization

    • Solved using bisection method for single variable problems
    • Solved using gradient based descent methods for multivariable problems with differentiable objective (e.g., Newton’s method)
    • Non-linear functions can lead to saddle points or sub-optimal solutions

subject to:

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Basics of Optimization

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Linear Programming

    • Feasible region represents a polyhedron
    • Solved using simplex method or interior point method
    • Exhibits strong duality
        • Dual problem are easier to solve and have economic interpretation especially if the primal problem is a resource allocation problem

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Integer Programming

    • Feasible region represents a set of points
    • Solved using branch and bound methods, cutting plane methods or a combination of the two
    • Relaxation of (iii) makes the problem LP but optimal solution may be infeasible for the IP

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Basics of Optimization

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Convex Programming

    • Objective function and constraints are convex functions
    • The feasible region is closed and bounded
    • The feasible region constitutes a convex set
    • KKT conditions are used to for checking optimality of the solution
    • Solved using interior point methods

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Computation complexity

    • Linear programming (LP) problems are the easiest to solve
    • Convex problems are relatively easy to solve compared to LP
    • Non-linear programs can be approximated as LP or convex problems and solved
    • Integer programs are NP hard due to the combinatorial nature

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Basics of Optimization

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Rules of Optimization

    • Make sure every constraint function and objective function are represented in terms of the decision variables
    • Make sure equality constraints have only linear expressions
    • A convex expression of the decision variables should be less than or equal to an affine function
    • A concave function of the decision variables should be greater than or equal to an affine function

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Selected Topics in Network Design

Cognitive Radio Networks – Basic Concepts

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Basic Concepts

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Origin of Cognitive Radio

    • This term was coined by Joseph Mitola in 1999
    • Mitola used adaptive signal processing and machine learning techniques in his PhD dissertation
      • This gave rise to the software defined radio (SDR)
      • The next logical step to control SDR based on upper layer protocols and vice versa
    • A network of cognitive radios is referred to as a cognitive radio network
    • Cognitive radio network became an active area of research by 2005-06
    • Cognitive radio networks have become very important in the evolution of wireless network design

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio

  • Cognitive radio sender statistically learns about the RF environment through the receiver feedback.
  • The sender and receiver adapt parameters accordingly to achieve the desired performance.
    • Learning can be implemented via both software and hardware
  • Here, machine learning or game-theory have become important
    • What can be achieved through learning?
    • What would be the tradeoffs?

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Spectrum usage

  • Early developments – Opportunistic networks which can operate anywhere (licensed and unlicensed spectrum)
  • Licensed spectrum such as TV spectrum became an ideal candidate
    • In Nov. 2002, the FCC published a report observing low spectrum utilization
    • Licensed spectrum (e.g., DVB-T; 54-862 MHz) was underutilized while unlicensed spectrum (2.4 GHz and 5 GHz) are crowded
    • In Oct 2008, FCC published results of radio prototypes which could detect unused portions of TV spectrum

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Spectrum usage

  • These cognitive radios operate in the unused portions of the TV spectrum (referred to as white spaces)
    • IEEE 802.11af allows wireless networks to operate in TV white spaces
  • However, wireless medium is unreliable which results in disruptions
  • The licensed users who are legitimate access to operate (e.g., TV receivers in TV spectrum) are called primary users
  • The unlicensed wireless network users opportunistically access TV white spaces are called secondary users

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Spectrum usage

  • Secondary users’ transmissions must be kept within permissible tolerance levels
  • Secondary users take responsibility of discovering white spaces
    • This is called spectrum sensing
  • Secondary users take responsibility of interference management
    • Via transmit power control or spectrum handoff
  • Secondary users implement the adaptive protocols for achieving their desired QoS

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Operations of secondary users

  • Cognitive radios in a network can share information about the wireless medium and perform opportunistic spectrum access
    • This referred to as dynamic spectrum access
    • Design of cognitive radio networks depends on the following:
      • Network architecture
      • Coexistence of SUs and PUs
      • Control channel configuration
      • Cooperation between SUs
      • Dynamic spectrum access scheme

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Relevance for the future

    • Design of next generation networks such as 5G+ have been motivated by CRN
      • Overlay versus underlay network
        • Example: Heterogeneous cellular networks
      • Dynamic resource allocation
      • Interference mitigation
      • Adaptive modulation and coding
      • Cooperative networks
      • Applications of machine learning and game-theory

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Cognitive Radio Networks – Basic Concepts

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Cognitive Radio Networks – Relevance for the future

    • Next generation networks extend concept of opportunistic access beyond spectrum
    • Opportunistic service provisioning:
      • Caching, computing, peer-peer file sharing, wireless charging, etc.
    • Opportunistic service discovery and access:
      • Example: Discovering edge resources, discovering services, opportunistic relaying, etc.

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Selected Topics in Network Design

Cognitive Radio Networks – Spectrum Sensing

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Spectrum Sensing

SELECTED TOPICS IN NETWORK DESIGN

Non-cooperative spectrum sensing

    • Spectrum sensing is a operation where an SU listens to a PU channel for transmissions over a small sensing duration
      • It can be pro-active or reactive

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing

    • Some minimum detection threshold must be specified for PU transmissions
      • PU receiver sensitivity is not known a priori
    • Sensing accuracy depends on:
      • Sensing duration
      • Channel propagation model
      • Sensitivity of the SU receiver
    • Spectrum sensing is affected by probability of false alarm and probability of miss detection

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing

    • Non-cooperative spectrum sensing means that each SU senses the channel and keeps the result to itself
    • The SDR design must have
      • High sampling rate
      • High resolution analog to digital converters (ADCs) with large dynamic range
      • High speed signal processors
      • Antenna and power amplifiers capable of operating over a wide range of frequencies
      • High speed processing units (DSPs or FPGAs)
    • SDR platforms: GNU Radio, Universal Software Radio Peripheral (USRP) and SSC’s XG Radio

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing – Cost versus complexity

    • Single radio architecture: Same radio for sensing and data transmission
    • Dual radio architecture: Separate radio dedicated for sensing and data transmission

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing – Energy based

    • Received signal is compared to an energy detection threshold
    • Advantages:
      • Simple, low cost and computation
    • Disadvantages:
      • Cannot distinguish between PU signal and interference
      • Performs poorly under low SNR and depends on threshold
      • Applicable when PU signal is spread

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing – Energy based

    • Let received signal be y(n) = s(n) + w(n)
      • s(n) and w(n) are the power of the received signal and the additive white Gaussian noise (AWGN) in time period n
    • The detection metric is the energy over N samples given by M = |y(0)|2 + |y(1)|2 +...+ |y(N)|2
    • The energy M is compared against a threshold λE
    • This is equivalent to distinguishing the two hypothesis

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing – Energy based

    • The performance is analyzed in terms of the two probabilities

    • Threshold λE can be set to the estimated noise variance
    • Noise variance is obtained as the smallest Eigenvalue of the incoming signal’s autocorrelation

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Cognitive Radio Networks – Spectrum Sensing

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Non-cooperative spectrum sensing – Waveform based

    • Depends on preambles or midambles in PU signal
    • The detection metric based on correlation is given by

    • Used when PU is IEEE 802.11b or WiMAX device

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Cognitive Radio Networks – Spectrum Sensing

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Cooperative spectrum sensing

    • SUs help one another by sharing their sensing results with one another on a low bandwidth common control channel
    • Soft data fusion techniques can be applied to calculate the status of the PU channel
        • Soft data fusion example: Neural networks, fuzzy logics, etc.
        • Hard data fusion techniques can also be used such as AND / OR / M-out-of-N rule
    • The reliability of spectrum sensing increases with the number of SUs that sense a PU channel

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Cognitive Radio Networks – Spectrum Sensing

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Cooperative spectrum sensing

    • Once, an SU learns the PU channel status within a frame duration, it can skip sensing that channel
        • Thus cooperative spectrum sensing saves SU’s energy
        • This also reduces sensing time compared to non-cooperative spectrum sensing
    • Cooperative sensing can be performed in centralized or distributed manner
        • In a centralized architecture, an SU BS collects sensing results and broadcasts them
        • In distributed architecture, SUs broadcast sensing results to one hop neighbors

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Selected Topics in Network Design

Cognitive Radio Networks – Cooperative Spectrum Sensing I

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Cooperative spectrum Sensing

SELECTED TOPICS IN NETWORK DESIGN

Centralized cooperation

    • Centralized cooperation requires a central controller and dedicated control channel
      • Central controller can be called cognitive base station
    • Consider implementing the cooperative spectrum sensing using a central controller
      • It is not necessary to implement cooperative spectrum sensing and dynamic spectrum access together
    • Some questions to be addressed:
    • What could be the objective?
    • What information is needed to implement this scheme?
    • What kind of decisions should be taken?
    • What kind of mathematical model will result?

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Roles of nodes

    • Centralized CRN consists of cognitive BS and SUs
    • Performance depends on the SU’s sensitivity, proximity to PU, number of SUs and number of channels

    • Role of BS:
      • Assigns (broadcast) SUs to sense PU channels
      • Collects sensing results from SUs
      • Estimates the status of the PU channels (e.g., OR)
      • Broadcasts the transmission schedule to all SUs
      • BS performs downlink transmissions

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Roles of nodes

    • Role of SUs:
      • Sense PU channels according to sensing schedule
      • Report the sensing results to the BS
      • Listen to the broadcast by BS and switch to corresponding idle PU channel
      • SUs send an ACK to the BS for successful reception

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Interaction between nodes

  • Frame structure repeats periodically
  • Sensing period is denote by △L
  • Let L denote the frame size and η denote the size of sensing schedule, downlink schedule and ACK reporting phase
  • The effective transmission time is given by L– k×△L – η where k represents the number of channels sensed by any user

Sensing schedule BS-SUs

Sensing phase

SUs-BS

Downlink schedule

Downlink transmission

ACK phase

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Mathematical model

  • Data: Number of SUs, number of PU channels, SU’s probability of miss detection (PMD) and SU’s probability of false alarm (PFA), ACKs received, PU channel status

  • Generation of PU channel status:

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Mathematical model

  • Decisions: Assignment variable to indicate SU m is assigned to PU channel n
    • Let amn denote the assignment variable
  • Objective: To maximize sum data rate of all downlink transmissions

    • Data rate depends on effective transmission time
    • Effective transmission time depends on sensing phase

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Mathematical model (contd.)

    • Size of sensing phase increases as number of SUs sensing a PU channel increases
    • Sensing accuracy increases as number of SUs sensing a PU channel increases
    • High sensing accuracy means increase in successful transmissions but lower throughput
      • Successful transmission means more ACKs received
  • Constraint 1:
    • Number of channels sensed by all users must be same

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Mathematical model (contd.)

    • This constraint ensures fairness to all SUs
  • Constraint 2:
    • Amount of time left for data transmission is sufficient

    • Interference to PU on channel n must be kept within its corresponding limit (ζ)

    • The miss detection probability is determined by the channel assignments of previous slots t-1, t-2,..., 0 and the lack of ACKs

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Expressing accuracy and its impact

  • The interference caused to the PU is expressed in terms of the probability of miss detection (PMD)

  • Here, PD(m,n) represents the detection probability which depends on detection threshold and propagation model
  • Data rate also depends on false alarm PFA(n)

    • Marcum Q functions and Gamma functions are used to get analytical expression for PMD and PFA

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Centralized cooperation – Expressing accuracy and its impact

  • False alarm PFA depends on the detection threshold and miss detection probability
  • PFA(n) and PMD(n) are improved (decreased) based on number of SUs assigned to a PU channel n (i.e., Σm amn)
  • In other words, maximizing the data rate is same as minimizing PFA(n) and PMD(n)

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Selected Topics in Network Design

Cognitive Radio Networks – Cooperative Spectrum Sensing II

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Cooperative spectrum Sensing

SELECTED TOPICS IN NETWORK DESIGN

Distributed cooperation

    • Distributed cooperation does not require central controller
      • Control channel can be configured in different ways
    • Distributed cooperation requires random access protocols
      • Examples: Slotted ALOHA, CSMA, etc.
    • Distributed cooperative spectrum sensing can achieve objectives similar to the centralized counterpart
      • Example: Maximizing sum data rates of all SU transmissions
    • Distributed cooperation is limited by the size of the network and random access scheme

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Distributed cooperation – Example

    • Consider a distributed network having a common control channel for all SUs
    • SUs consist of two transceivers one tuned to a dedicated control channel and another to an idle PU channel
    • The SUs cooperate to sense the idle PU channels and contend for transmission using a winner-takes-all strategy
    • A common frame structure is followed by all the SUs in the neighbourhood
    • Define the requirements

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Components and their roles

    • SUs are the only components present in the network
    • Broadcasts by an SU is heard by its one hop neighbor
    • SUs maintain a list of PU channels to be sensed
    • SU randomly picks one of the remaining channels to be sensed
    • Performs sensing (e.g., energy detector) for small duration
    • Broadcast the result to its neighbours
    • Upon receiving a broadcast, an SU updates its list of channels to be sensed
    • Upon receiving the broadcast, an SU performs local fusion of the sensing results (e.g., OR)

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Interaction between the nodes

    • A common frame is assumed for all nodes

Ts = TRP + TNP = n × Tms + TNP

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Objective

    • To maximize the throughput for an SU winning the contention
    • How to define throughput (η)?

η = E{i} × R × TNP / TS

Average number of channels sensed idle

Link rate per channel (bps)

Data transmission time

Slot duration

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Objective – Calculation of E{i}

    • Let us consider u SUs sensing n PU channels
    • For simplicity, lets assume each PU channel has a busy probability of γ
    • Let P(i) denote probability of sensing i PU channels as idle

    • The average number of idle PU channels is given by

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Objective – Optimal TNP

    • Estimation of TNP depends
      • Average number of transitions into idle state
      • Average number of transitions into collision state
      • Average number of transitions into successful state

      • Here, the time durations are calculated as follows

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Objective – Optimal TNP

    • Estimation of TNP (contd.)
      • Let p denote the transmit probability as per p-persistent CSMA
      • Then, the probabilities of idle, collision and success are expressed as

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Cognitive Radio Networks – Cooperative spectrum Sensing

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Analysis – Cooperative spectrum sensing with winner-takes-all strategy

    • How to ensure fairness in spectrum sensing?
    • What happens when the number of SUs increase?
    • What happens when the number of PU channels increases?
    • What are the remedies?

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Selected Topics in Network Design

Cognitive Radio Networks – Network Architectures I

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Network Architectures I

SELECTED TOPICS IN NETWORK DESIGN

Centralized CRN

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Cognitive Radio Networks – Network Architectures I

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Centralized CRN

    • Consists of cognitive base stations and SUs
    • Each BS manages the activities of its cell
    • The BSs may have direct connection or connected to a central controller via a backhaul network
    • Roles of BS:
      • Cooperative spectrum sensing
      • Scheduling of idle PU channels for uplink and downlink
      • Admission control
      • Synchronization
      • Handoff management
      • Quality of service (QoS) guarantee
      • Load balancing

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Cognitive Radio Networks – Network Architectures I

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Centralized CRN (contd.)

    • BS operations are scheduled by a frame structure
    • Base station and SUs require a common control channel for exchange of global control messages
      • Examples of global control messages: Beacon, uplink requests, scheduling grants, handoff messages, discovery messages, etc.
    • Common control channel is usually a dedicated low rate channel established in the unlicensed spectrum
    • Local control messages can be carried out on idle PU channels
      • Examples of local control messages: RTS, CTS, ACK, etc.

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Cognitive Radio Networks – Network Architectures I

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Centralized CRN (contd.)

    • In several centralized CRNs, an SU is assumed to follow dual radio architecture
    • What happens when a single radio architecture is used?
    • Other questions
      • What happens when the number of SUs increases?
      • What happens when the number of PU channels increases?
      • Should the spectrum access be guaranteed or random?
      • What is the impact of the low bit rate control channel?
      • What kind of security threat exist?
      • What kind of remedies will be helpful?

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Cognitive Radio Networks – Network Architectures I

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN

    • Cognitive base stations are not present
    • May (or may not) have control channel for coordination
    • Suffer from latency issues
    • An SU in distributed CRN performs the following
        • Identify neighbours
        • Perform spectrum sensing
        • Broadcast sensing results with neighbours
      • Handshake/negotiate with other SUs
      • Uses MAC protocols for coordination
      • Address hidden node problems

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Cognitive Radio Networks – Network Architectures I

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN

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Cognitive Radio Networks – Network Architectures I

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – Control channel configurations

    • Common control channel
      • Similar to centralized CRN
      • Dedicated channel for global control messages
    • Local control channels
      • One of the idle PU channels is chosen temporarily
      • SUs within one hop share a local control channel
      • Frame structure and usage per control channel is independent
    • No control channel
      • SUs use same idle PU channel for all purposes
      • SUs use random access protocol

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Cognitive Radio Networks – Network Architectures I

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – Control channel configurations

    • What will be the pros and cons of each approach?
      • Judge each approach in terms of
        • Cooperative spectrum sensing
        • Synchronization
        • Node discovery
        • Handoff and admission control
        • Spectrum access options
        • QoS support
        • Multi-hop communication

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Selected Topics in Network Design

Cognitive Radio Networks – Network Architectures II

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

    • SUs form a distributed network by broadcasting their information

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

    • Major steps: Node discovery, control channel setup and network formation

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

    • Frame structure

    • Beacon provides time synchronization, channel assignment and schedule for operations in the rest of the frame
    • NBP provides information about cluster member
    • DP provides TDMA based channel access for cluster members
    • QP is the synchronized sensing period

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

    • Frame structure (contd.)

    • Private and public RAP are meant for inter-cluster communication
      • Details given in next slide
    • New SUs are admitted during public RAP

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

    • Inter-cluster communication

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Cognitive Radio Networks – Network Architectures II

SELECTED TOPICS IN NETWORK DESIGN

Distributed CRN – CogMesh protocol

  • Can we modify the protocol to work without control channel?
  • Suppose each SU is battery driven. Provide a dynamic strategy for electing a new cluster head for extending the network life time.
  • Can we replace TDMA in DP with random access?
  • Can we replace random access in RAPs using TDMA?
  • What happens when the number of SUs is very large compared to the number of channels? How to address this issue?

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Selected Topics in Network Design

Cognitive Radio Networks – Multi-Channel Communication

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

What is multi-channel communication?

    • When multiple channels are available for transmission, sender may pick one/more channels using receiver’s feedback
      • Higher data rate can be achieved by using more channels
      • Use the best channel/channels for the transmission
    • When multiple sender-receiver pairs are present, a central controller can easily address the concerns of all nodes
    • How do we address this requirement in a distributed network?

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Challenges in distributed network

    • Coordination problems must be mitigated
      • Hand-shaking between sender and receiver
      • Synchronization issues between senders, receivers and their neighbours
      • Nodes may conserve power and go to sleep
      • Common control channel may or may not be preferred
    • Overhead due to control messages should be minimized
    • Channel switching must be minimized
    • Load balancing must be achieved

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Addressing the challenges

    • Consider each node only has a single half-duplex transceiver and a common control channel
    • Lets, look at a three step approach
      • IEEE 802.11 Power saving mode
      • Add the multi-channel communication requirement
      • Extend the above concept to the context of CRNs

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

IEEE 802.11 power saving mode

    • ATIM: Ad hoc Traffic Indication Messages

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC: Multi-channel MAC for multi-hop communication
    • Nodes maintain preferred channel list (PCL)
    • Channels are classified as LOW, MID and HIGH
    • One of the channels is referred to as default channel
    • M-MAC has two important steps
      • PCL update
      • Channel negotiation (MAC protocol)
        • Channel selection algorithm

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC – PCL update
      • Initial status of all channels is set to MID as they have not been used
      • If a sender-receiver pair have agreed to use a channel for first time then that channel status is made HIGH
      • If a sender-receiver find that some other nodes chose same channel then channel status is made LOW
      • If channel status is LOW then count the number of sender-receiver pairs which selected that channel

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC – Channel negotiation

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC – Channel selection algorithm
    • Let A-sender and B-receiver
    • If there is a HIGH state channel in B’s PCL, this channel is selected.
    • Else if there is a HIGH state channel in A’s PCL, this channel is selected.
    • Else if there is a channel which is in the MID state at both A and B, it is selected.
    • Else if there is a channel which is in the MID state at only one side (i.e., A or B) it is selected.

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC – Channel selection algorithm (contd.)
    • If all of the channels are in the LOW state, add the counters of the sender’s PCL and the receiver’s PCL. The channel with the least count is selected.
    • In any stage, ties are broken arbitrarily.

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Introducing multichannel communication requirement

    • M-MAC – Q and A
    • Suppose channels are negotiated between A and B first and then between A and C next. A is the sender in both cases.

    • In which order should A transmit to minimize HOL blocking ?
    • How to handle channel switch within a beacon interval if a transmission completes?
    • How to achieve load balancing?

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Cognitive Radio Networks – Multi-Channel Communication

SELECTED TOPICS IN NETWORK DESIGN

Extending the M-MAC concept to CRN

    • An SU in a distributed CRN performs cooperative spectrum sensing and spectrum handoff
    • When performing channel switching an SU can interfere with other ongoing SU transmissions or with the PU
      • This means multi-channel hidden terminal problem
    • Considerations:
      • Single transceiver and local control channels (as in CogMesh)
      • Two transceivers and dedicated common control channel
      • Load balancing can be achieved similar to M-MAC

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Selected Topics in Network Design

Cognitive Radio Networks – Admission Control I

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

What is admission control?

    • Admission control deals with resource allocation under arrival and departure events
    • Admission control policy is often analyzed using Markov chains because the arrival process and departure process are treated as independent and identically distributed
    • Important performance measures such as blocking probability and termination probability can be studied in a lossy system
    • Important performance measures such as blocking probability and queuing delay can be studied in a lossless system

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Consider a system with M PU channels which can be divided into MN sub-channels
    • Each SU requires one sub-channel while each PU requires one channel

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Assumptions
      • Let λp, λ1 and λ2 denote the mean arrival rates of PU, SU1 (high priority) and SU2 (low priority) respectively
      • Let μp, μ1 and μ2 denote the mean service rates of PU, SU1 and SU2 respectively
      • ζ number of sub-channels are reserved for the SU1 arrivals
        • That means, when number of idle sub-channels in the system is less than or equal to ζ then SU2 arrival is blocked
      • Call arrivals and service times are Markovian

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Operations – Arrivals and departures
      • A PU is allocated a channel only if k < M
      • An SU1 call is allotted one sub-channel only if Y < MN
      • An SU2 call is allotted one sub-channel only if Y < MN-ζ
      • When PU call is accepted, then l SU1 calls and m SU2 calls are displaced
      • The displaced calls are handed off according to their priority
      • When PU call ends, N sub-channels are released
      • When a SU call ends, one sub-channel is released

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Operations – handoff
    • When l SU1 calls and m SU2 require handoff upon a PU arrival handoff is performed

    • First determine the number of available sub-channels

    • First allocate idle sub-channels (if any) to displaced SU1 calls followed by displaced SU2 calls.
    • Terminate the calls when idle sub-channels are unavailable

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • No. of displaced SU calls experiencing failure in handoff is given by

    • The number of SU1 calls dropped due to failure is given by

    • The number of SU2 calls dropped due to failure is given by

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Determining state transitions – SU arrivals
    • Assume the state is (i, j, k) so number of busy sub-channels Y = i + j + k*N
    • Transition (i, j, k) 🡪 (i+1, j, k) occurs with rate λ1 provided Y < M*N
    • Transition (i-1, j, k) 🡪 (i, j, k) occurs with rate λ1 provided Y < M*N
    • Transition (i, j, k) 🡪 (i, j+1, k) occurs with rate λ2 provided Y < M*N – ζ
    • Transition (i, j –1, k) 🡪 (i, j, k) occurs with rate λ2 provided Y < M*N – ζ

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Determining state transitions – SU departures
    • Transition (i+1, j, k) 🡪 (i, j, k) occurs with rate (i+1)μ1
    • Transition (i, j, k) 🡪 (i–1, j, k) occurs with rate (i)μ1
    • Transition (i, j+1, k) 🡪 (i, j, k) occurs with rate (j+1)μ2
    • Transition (i, j, k) 🡪 (i, j–1, k) occurs with rate (j)μ2

    • Determining state transitions – PU departure
    • Transition (i, j, k+1) 🡪 (i, j, k) occurs with rate (k+1)μp
    • Transition (i, j, k) 🡪 (i, j, k–1) occurs with rate (k)μp

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Determining state transitions – PU arrival
    • Transition (i, j, k–1) 🡪 (i, j, k) occurs with rate λp only when Y ≤ N(M–1)
      • All displaced SU call get successful handoff
    • Transition (i, j, k) 🡪 (i-l’, j-m’, k+1) occurs with rate when N(M–1) < Y MN
      • The above transition rate is calculated as follows
      • Example: Let M = 3, N = 2, i = 1, j = 2 and k = 1 then possible cases of SUs before handoff

PU

1 SU1 , 1 SU2

1 SU2

PU

2 SU2

1 SU1

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Determining state transitions – PU arrival
    • Displacements by incoming PU

    • After handoff

    • So (1, 2, 1) 🡪 (1, 1, 2) with rate (3/4) λp whereas (1, 2, 1) 🡪 (0, 2, 2) with rate (1/4) λp

PU

1 SU1, 1 SU2

1 SU2

PU

1 SU1, 1 SU2

1 SU2

PU

2 SU2

1 SU1

PU

2 SU2

1 SU1

PU

PU

1 SU1, 1 SU2

Displaced

Dropped

l = 1, m = 1

l ‘= 0, m’ = 1

l = 0, m = 1

l ‘= 0, m’ = 1

l = 0, m = 2

l ‘= 0, m’ = 1

l = 1, m = 0

l ‘= 1, m’ = 0

PU

PU

2 SU2

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

  • Blocking probability

  • Probability of forced termination

PF2

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Selected Topics in Network Design

Cognitive Radio Networks – Admission control II

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Cognitive Radio Networks – Admission control II

SELECTED TOPICS IN NETWORK DESIGN

Case study – Call admission control

    • Suppose there are two types of SUs in the system SU1 and SU2
    • Suppose SU1 has higher priority over SU2 and has same admission control policy as in the previous example
    • Unlike the previous example, during handoff of SU1 when idle sub-channels are not available, some ongoing SU2 calls can be terminated to make way for the displaced SU1 calls
    • Model the call admission control as CTMC
    • Derive the blocking probability and throughput

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • The channel and sub-channel specification are the same as previous example
    • Call admission policy of SUs and PUs are same as pervious example
    • SU1 has sub-channel reservation of ζ

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Handoff policy
      • When l SU1 calls and m SU2 require handoff upon a PU arrival handoff is performed

      • Find the idle sub-channels in the system

      • Allocate min(r, l) SU1 calls to the idle sub-channels randomly
      • For the remaining l – min(r, l) SU1 calls, check if any SU2 calls are ongoing

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Handoff policy (contd.)
      • Terminate the min(j – m, l – min(r, l)) SU2 calls and allocate some of the remaining displaced SU1 calls
      • If there are no ongoing SU2 calls, the remaining displaced SU1 calls are terminated.
      • When there is no idle sub-channel, the remaining displaced SU2 calls are terminated
      • The terminated SU1 and SU2 calls are given by

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • State transitions
      • The state transitions are identical to the previous example except for the expressions for l’ and m’

    • Example of termination
      • Let M = 3, N = 2, i = 1, j = 2 and k = 1 then possible cases of SUs before handoff

PU

1 SU1 , 1 SU2

1 SU2

PU

2 SU2

1 SU1

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Determining state transitions – PU arrival
    • Displacements by incoming PU

    • After handoff

    • So (1, 2, 1) 🡪 (1, 1, 2) with rate (4/4) λp or simply λp

PU

1 SU1, 1 SU2

1 SU2

PU

1 SU1, 1 SU2

1 SU2

PU

2 SU2

1 SU1

PU

2 SU2

1 SU1

PU

PU

1 SU1, 1 SU2

Displaced

r

Dropped

l = 1, m = 1

1

l ‘= 0, m’ = 1

l = 0, m = 1

0

l ‘= 0, m’ = 1

l = 0, m = 2

1

l ‘= 0, m’ = 1

l = 1, m = 0

1

l ‘= 0, m’ = 1

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • State transition diagram

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Comparison of the call admission control policies

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Comparison of the call admission control policies

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Cognitive Radio Networks – Admission control

SELECTED TOPICS IN NETWORK DESIGN

Case study – Priority based admission control and handoff

    • Comparison of the call admission control policies

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Selected Topics in Network Design

Wireless Wide Area Networks (WWAN) – Introduction

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless wide area networks – Introduction

SELECTED TOPICS IN NETWORK DESIGN

What are WWANs?

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Wireless wide area networks – Introduction

SELECTED TOPICS IN NETWORK DESIGN

How does a base station look?

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Wireless wide area networks – Introduction

SELECTED TOPICS IN NETWORK DESIGN

WWAN architecture

To provide voice, internet and other services via wireless communication

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Wireless wide area networks – Introduction

SELECTED TOPICS IN NETWORK DESIGN

WWAN architecture

    • The coverage of wireless WAN is referred to as macrocell
    • Wireless WAN consists of MBSs, central office, switching equipment and gateway routers
    • MBS can have multiple antennas (RF module) which are connected with servers
    • Servers perform functions of baseband module, control and signalling, radio resource allocation, handoff, admission control, load balancing, etc.
      • Servers may be co-located with antennas in the site

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Wireless wide area networks – Introduction

SELECTED TOPICS IN NETWORK DESIGN

WWAN architecture

    • MBS of different cells can be connected to one another directly or indirectly
        • These connections can be wired or wireless
    • Central office maintain user details (e.g., location, subscription, etc.), routes, etc.
    • Gateway routers connect different ISP networks and also connect to the core network (internet)
    • The MBS, wireless links and wireless users in the cell site are collectively known as fronthaul
    • The mobile operator’s network excluding the fronthaul is called backhaul network

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Selected Topics in Network Design

Wireless Wide Area Networks (WWAN) – Design aspects

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

What are the main design aspects of WWANs?

    • Energy efficiency
    • Radio resource allocation
    • Radio resource utilization
    • Traffic congestion management
    • Service delivery
    • Protocols for broadcast and multicast transmission

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

What is energy efficiency?

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Remedies for energy efficiency

    • Manufacturers are focusing on devices that consume less and whose consumption is more load proportional

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Remedies for energy efficiency

    • RRH is a layout in which the RF and PA are in the cell site
    • Advantages of RRH: Feeder losses are minimized and cooling requirement is minimized
    • Some recent approaches try to integrate BBU of various BSs into a single unit
    • So BBU and PA power consumption must be optimized

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Remedies for energy efficiency

    • Energy efficiency can be achieved by
      • Turning the BS off strategically
      • Energy harvesting
      • Cooperative techniques
        • MIMO techniques
        • Heterogeneous networks
        • Energy/data offloading

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Sleep mode challenges

  • Incorporating sleep mode means extra cost for network operator
  • Switching off a BS and using a larger cell might lead to a lower signal strength
  • Energy saved by the on/off switching is thus traded off for more energy being drained from the user end
  • Hence, good BS management algorithms are required taking all above aspects into account

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Energy harvesting challenges

  • Energy harvesting reduces the energy costs as the grid power consumption is reduced
  • Energy harvesting can be applied for MBS configuration or for BBU-RRH configuration.
  • The harvested energy is random (spatially and temporally)
  • The BS management algorithm, network protocols and transport protocols have to be modified

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Wireless wide area networks – Design aspects

SELECTED TOPICS IN NETWORK DESIGN

Cooperative techniques

  • Cooperation is key to interference management and improving the performance of the radio resource allocation
  • Cooperation arises in several network scenarios
  • However, cooperation requires a win-win strategy for all participants
  • Cooperation requires central controller, common control channel, backhaul network management and incentives
  • Cooperation results in large overhead but also benefits

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Selected Topics in Network Design

Long term evolution (LTE) – PHY and frame format

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE introduction

    • Referred to as 4G cellular technology
    • All IP based service for voice and data
      • Only supports packet switched services
    • 3GPP launched the LTE (aka evolved universal terrestrial access (E-UTRA)) in 2004 (Rel. 8)
    • Achievable peak data rates 300 Mbps (downlink) / 75 Mbps (uplink)
    • Improved spectrum efficiency (15 for DL / 3.75 for UL)
    • Frequency bands: 1800 MHz, 1900 MHz, 2.1-2.5 GHz, etc.
    • Operates in TDD / FDD mode

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE introduction

    • Orthogonal frequency division multiple access (OFDMA) is used in downlink.
    • Single carrier frequency division multiple access (SC-FDMA) is used for uplink
    • Release 10 (2010) added several features, which are collectively known as LTE-Advanced

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE – Resource element

  • The basic unit of resource grid
  • Each RE spans one symbol by one subcarrier
  • Each RE usually carries two, four or six physical channel bits, depending on whether the modulation scheme is QPSK (2 bits), 16-QAM (4 bits) or 64-QAM (6 bits)

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE – Bandwidth options

  • A cell can be configured with several different bandwidths

Example: 5 MHz bandwidth has 25 RBs and transmission bandwidth is 25 × 180 kHz = 4.5 MHz

This leaves 0.5 MHz which is distributed as two 0.25 MHz guard bands

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Selected Topics in Network Design

Long term evolution (LTE) – PHY and frame format

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

390 of 553

LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE introduction

    • Referred to as 4G cellular technology
    • All IP based service for voice and data
      • Only supports packet switched services
    • 3GPP launched the LTE (aka evolved universal terrestrial access (E-UTRA)) in 2004 (Rel. 8)
    • Achievable peak data rates 300 Mbps (downlink) / 75 Mbps (uplink)
    • Improved spectrum efficiency (15 for DL / 3.75 for UL)
    • Frequency bands: 1800 MHz, 1900 MHz, 2.1-2.5 GHz, etc.
    • Operates in TDD / FDD mode

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE introduction

    • Orthogonal frequency division multiple access (OFDMA) is used in downlink.
    • Single carrier frequency division multiple access (SC-FDMA) is used for uplink
    • Release 10 (2010) added several features, which are collectively known as LTE-Advanced

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE – Resource element

  • The basic unit of resource grid
  • Each RE spans one symbol by one subcarrier
  • Each RE usually carries two, four or six physical channel bits, depending on whether the modulation scheme is QPSK (2 bits), 16-QAM (4 bits) or 64-QAM (6 bits)

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LTE – PHY and frame format

SELECTED TOPICS IN NETWORK DESIGN

LTE – Bandwidth options

  • A cell can be configured with several different bandwidths

Example: 5 MHz bandwidth has 25 RBs and transmission bandwidth is 25 × 180 kHz = 4.5 MHz

This leaves 0.5 MHz which is distributed as two 0.25 MHz guard bands

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Selected Topics in Network Design

Long term evolution (LTE) – Logical channels and reference signals

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Data channels and logical channels

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Logical channels

    • One RB has 12 sub-carriers with 14 OFDM symbols each (assuming normal CP).
      • In other words, 168 REs (i.e., 12 × 14)
    • The actual number of usable REs for data depend on the size of the control region where all PDCCH reside and the number of RBs
    • Example: 3 OFDM symbols per sub-carrier are meant for control channels while remaining are used for data channels

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Logical channels - Types

  • PDCCH: Physical downlink control channel
  • PUCCH: Physical uplink control channel
  • PRACH: Physical random access channel
  • PDSCH: Physical downlink shared channel
  • PUSCH: Physical uplink shared channel
  • PHICH: Physical Hybrid ARQ Indicator Channel
  • PCFICH: Physical Control Format Indicator Channel

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Logical channels - Roles

  • PUSCH and PDSCH are data channels for uplink and downlink transmissions respectively
  • PDCCH is used to provide physical layer signalling to support the MAC layer operation
  • PDCCH carries a message known as the downlink control information (DCI)
    • Control channels must be robust so that a control message is correctly received anywhere in a cell
  • PDCCH does not have the luxury of HARQ
    • UE only has one chance to decode its PDCCH

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Reference signals

  • Uplink reference signals are classified as
      • Scheduling Requests (SR)
      • Buffer Status Reports (BSR)
      • Power Headroom Reports (PHR)
      • Sounding Reference Signal (SRS)
      • Channel Quality Indicator (CQI)
      • Demodulation Reference Signal (DMRS)

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Reference signals

  • Scheduling Requests (SR):
      • Used to distinguish active users with data in their buffers from idle users.
      • Each user with data pending in its buffer sends a one bit SR to the eNB informing of its need for an uplink grant to be scheduled.
  • Buffer Status Reports (BSR):
      • Informs the eNB the amount of data a UE needs to send.
      • The report can be made either per group of (aggregated) radio bearers or per four groups.

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Reference signals

  • Power Headroom Reports (PHR):
      • Informs the eNB about the available power at the UE for scheduling and RRM.
  • Sounding Reference Signal (SRS):
      • Introduced in uplink LTE as a wide-band reference signal
      • Typically transmitted in the last SC-FDMA symbol of a 1 ms subframe
      • Used to provide information on uplink channel quality.
      • User data transmission is not allowed in this block, which results in an about 7% reduction in uplink capacity.

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LTE – Logical channel and reference signals

SELECTED TOPICS IN NETWORK DESIGN

Reference signals

  • Channel Quality Indicator (CQI):
      • A measurement of the channel quality between the UE and the eNB.
  • Demodulation Reference Signal (DMRS):
      • Used for channel estimation when coherent detection and demodulation is needed.
      • For the PUSCH, the DMRS has the same bandwidth as the uplink data transmission and occupies the fourth SCFDMA symbol for each uplink subframe.

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Selected Topics in Network Design

Long term evolution (LTE) – Scheduling operations

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

Basis for scheduling

  • MAC in eNodeB includes the dynamic resource scheduler to allocate the RBs to the UEs
      • That is, allocate PDSCH for downlink data traffic and PUSCH for uplink data traffic
  • The dynamic resource scheduler takes the following into account
      • Traffic volume
      • QoS requirement of UEs
      • Wireless channel quality
    • Downlink : Transmissions from base station to end users
    • Uplink: Transmissions from end users to base station

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

Downlink scheduling

  • The eNodeB transmits the PDSCH grant on PDCCH, and the data packet on the PDSCH accordingly
      • A PDSCH grant consists of PDSCH resource assignments and their modulation and coding scheme (MCS)
  • An UE first reads PCFICH every subframe to determine the number of OFDM symbols occupied by the control region
  • The UE monitors its PDCCH in the control region to discover its grant
  • Once its PDCCH is detected, the UE decodes the corresponding PDSCH using the required MCS
  • Depending on whether the decoding is successful, an UE sends ACK or NAK on PUCCH

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

Downlink scheduling (contd.)

  • If a NAK is detected by the eNB, it retransmits the data in a HARQ fashion
    • The UE combines the multiple received copies and tries to decode again
  • This process repeats until the data packet is successfully decoded

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

Uplink scheduling

  • An UE sends a scheduling request (SR) to an eNodeB via PUCCH if the PUCCH resource is already assigned
      • If a PUCCH is not configured for the UE, the UE sends the request through the PRACH
  • Thereafter, it monitors the PDCCH for the PUSCH resource assignments
  • An eNodeB receives SRs and assigns PUSCH resources and the associated MCS via PDCCH
  • Once a valid PDCCH is detected, an UE sends data on PUSCH based on the assignments

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

Uplink scheduling (contd.)

  • If the eNB decodes the data on PUSCH successfully, it sends ACK (or NAK, otherwise) on the PHICH
  • A NAK will trigger a HARQ retransmission process until the eNB successfully decodes the data packet

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LTE – Scheduling operations

SELECTED TOPICS IN NETWORK DESIGN

QoS and services

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Selected Topics in Network Design

Long term evolution (LTE) – Network Architecture

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Introduction

  • LTE follows centralized architecture consisting of the access network and core network
  • LTE system is also known as evolved packet system (EPS)
  • It provides privacy & security for users and network equipment against fraudulent use
  • EPS uses the EPS bearers to route IP traffic from PDN to UE

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Network architecture

EPC

EUTRAN

EUTRAN: Evolved universal terrestrial access network

EPC: Evolved packet core

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Alternate view of the network architecture

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Links/interfaces

Interfaces between the components

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Network architecture – Components

  • The main components of the EPC are:
      • PDN Gateway (P-GW)
      • Serving Gateway (S-GW)
      • Mobility Management Entity (MME)
      • Home Subscriber Server (HSS)
      • Policy Control and Charging Rules Function (PCRF)
  • The main components of the EUTRAN are:
    • eNodeB
    • UEs

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Functions of EPC components

    • PDN Gateway (P-GW)
      • IP address assignment for UE
      • QoS enforcement and flow-based charging
      • Filtering of downlink user IP packets into the different QoS-based bearers
      • Serves as the mobility anchor for interworking with non-3GPP technologies

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Functions of EPC components

    • Serving Gateway (S-GW)
      • All IP packets are transferred through the S-GW
      • Serves as the local mobility anchor for the data bearers during handoff
      • Serves as the mobility anchor for interworking with other 3GPP technologies

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Functions of EPC components

  • Mobility management entity (MME)
      • It is the control node that processes the signalling between the UE and the EPC
      • MME protocols are known as the non-access stratum (NAS) protocols
      • Operations of MME are classified as bearer management and connection management
          • Bearer management deals with establishment, maintenance and release of bearers
          • Connection management deals with establishment of connection and security between the network and UE

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Functions of EPC components

  • Policy Control and Charging Rules Function (PCRF)
      • It is responsible for policy control decision-making
      • and flow-based charging
      • It provides the QoS authorization according to the user’s subscription profile

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LTE – Network Architecture

SELECTED TOPICS IN NETWORK DESIGN

Functions of EPC components

  • Home Subscriber Server (HSS)
      • It contains users’ EPS-subscribed QoS profile and any access restrictions for roaming
      • It also holds information about the PDNs to which the user can connect.
          • This could be in the form of an access point name (APN) or a PDN address (subscribed IPs)
      • It holds dynamic information such as the identity of the MME to which the UE is currently associated

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Selected Topics in Network Design

Long term evolution (LTE) – EUTRAN, logical functions and admission control

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

EUTRAN

  • The E-UTRAN is responsible for all radio related functions such as
      • Radio resource management (RRM)
      • Header Compression
      • Security
      • Connectivity to the EPC

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

EUTRAN - RRM

    • Radio bearer control
    • Radio admission control
    • Radio mobility control
    • Scheduling and dynamic allocation of resources to UEs in both uplink and downlink
    • Inter-cell interference coordination (ICIC)

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Logical functions

    • E-UTRAN operations is divided into control plane and user (or data) plane
    • Control plane deals with carrying control messages pertaining to the EUTRAN or EPC
    • Data plane deals with carrying control messages dealing with exchange of data packets between a client in the EPS and an external host
    • Control plane functions: RRC and NAS
    • User plane functions: PDCP, RLC, MAC, PHY

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Logical functions

    • Control plane:
      • It control the radio access bearers and the connection between the UE and the network
    • Control plane – Radio Resource Control (RRC)
      • Deals with link setup, mobility and handoff and scheduling broadcast within the access network (i.e., EUTRAN)
      • Deals with the assignment of radio resources (i.e., PRBs) to logical uplink and downlink control channels and data channels

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Logical functions

    • Control plane – Non-Access Stratum (NAS)
    • Relay control messages between the UEs and MME
    • Bearer management for the UEs
    • Authentication
    • Paging and mobility management when the UE is in the idle state
    • Security control

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Logical functions

    • User plane – Packet Data Convergence Protocol (PDCP)
      • Ciphering and integrity protection, transfer of control plane data
    • User plane – Radio Link Control (RLC)
    • Correction (ARQ)
    • Concatenation, segmentation and reassembly for RLC segments
    • Reordering and duplication detection

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Logical functions

    • User plane – Medium Access Control (MAC)
      • Maps logical channels and transport channels
      • Multiplexing and scheduling MAC segments
      • Relaying scheduling information
      • Error correction (HARQ)
      • Priority handling
    • User plane – Physical Layer (PHY)
      • Carries all information from the MAC transport channels over the air interface
      • Deals with link adaptation (AMC), power control, cell search and other measurements for the RRC layer

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

Admission control

  • When an UE attaches to an LTE network, it is assigned an IP address by P-GW and at least one bearer is established
      • This is called the default bearer
  • The QoS parameter values of the default bearer are assigned by the MME based on user subscription data retrieved from the HSS.
  • The QoS parameter values for dedicated bearers are received by the P-GW from the PCRF and forwarded to the S-GW.
  • The MME only transparently forwards those values received from the S-GW over the S11 reference point
  • When handoff is initiated, the bearer establishment with the new eNodeB must be initiated via the MMEs

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LTE – EUTRAN, logical functions and admission control

SELECTED TOPICS IN NETWORK DESIGN

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Selected Topics in Network Design

Long term evolution (LTE) – Enhancements

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

433 of 553

LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Introduction

  • LTE with its enhancements since release 8 are known as LTE-Advanced
  • The various enhancements are given by
      • Clustered SC-FDMA
      • Carrier aggregation
      • Coordinated multipoint transmission/reception
      • Device to device (D2D) communication

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Clustered SC-FDMA

  • Recall, LTE assigned contiguous group of sub-carriers to UE
  • The transmit power was uniformly allocated across the assigned sub-carriers to a UE
  • The data rate was based on this uniform transmit power
  • LTE-Advanced enhances the uplink multiple access by adopting clustered SC-FDMA
  • Non-contiguous groups of sub-carriers can be allocated to UE for uplink data transmission
  • This enhances spectral efficiency

  • What are the challenges?

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Carrier aggregation (CA)

  • LTE-Advanced proposed to increase in the downlink rate by combining the sub-carriers across multiple carriers
  • The RRM can be modified to include carrier aggregation
  • Types of carrier aggregation
      • Intra-band contiguous CA
      • Intra-band non-contiguous CA
      • Inter-band non-contiguous CA

    • What are the advantages and challenges?

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Coordinated multipoint transmission (CoMP)

  • Multiple LTE base stations coordinate in measurements and/or data transmission

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Coordinated multipoint transmission

  • CoMP can be classified as: a) Coordinated scheduling and coordinated beam forming, b) Joint transmission and c) Transmission point selection

What are the challenges?

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Device to device communication (D2D)

  • UEs in close proximity (e.g., 25 meters) can communicate directly
  • D2D can significantly improve spectral efficiency while reducing the traffic load in the core network
  • Other advantages of D2D
    • offload cellular traffic
    • better system throughput
    • higher energy efficiency
    • relaying cell edge transmissions to the eNodeB
    • robustness to infrastructure failures
    • offer new services and applications

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LTE – Enhancements

SELECTED TOPICS IN NETWORK DESIGN

Device to device communication (D2D)

What are the challenges?

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Selected Topics in Network Design

Long term evolution (LTE) – D2D case study

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Problem description

  • Consider an LTE system in which the eNodeB allocates resource blocks for the cellular users and D2D users.
  • The resource blocks allocated to cellular users must be orthogonal to one another.
  • At most one D2D user is allowed to share the resource blocks allocated to a cellular user and vice versa.
  • Transmission is allowed only when SINR requirement is satisfied.
  • Define the data, decision variables, notations, objective and constraints.

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

System model: D2D scheduling

  • eNodeB schedules uplink and downlink transmissions
  • eNodeB also schedules D2D communication

Gd’d

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Roles of nodes

  • Some UEs send uplink requests on PUCCH or PRACH
  • eNodeB estimates pathloss for each uplink channel using DMRS signals
  • eNodeB finds pathloss for each downlink channel using CQI
  • eNodeB determines the RBs for uplink and downlink
  • eNodeB determines the corresponding transmit power (or MCS) for the RBs
  • eNodeB broadcasts the scheduling results via PDCCHs

Interaction between the nodes

  • Via LTE frame

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Data and notations

    • Let k denote the index of an RB
    • Let 𝒦up and 𝒦dn denote set of RBs dedicated for uplink and downlink transmissions
    • Let c and d denote index of cellular and D2D users respectively
    • Cellular users belong to the set 𝒞up and 𝒞dn
    • D2D pairs belong to the set 𝒟 = {1,...,D}

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Data and notations (contd.)

    • Channel gains of different wireless links are denoted by GBc, GcB, Gdc and GdB
    • SINR threshold for uplink cellular, downlink and D2D receivers are denoted by γB, γc and γd respectively
    • Transmit power for uplink cellular, downlink and D2D receivers are denoted by PB, Pc and Pd respectively

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Decisions and notations

    • Binary variable xck to represent the assignment of RB k to cellular user c
    • Binary variable ydk to represent the assignment of RB k to D2D user pair d
    • Continuous variables pck and pdk represent transmit power for cellular users and D2D transmitters respectively

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Objective

    • Maximize the sum data rate of all cellular users and D2D user-pairs

Numerators are received powers

Interference from uplink transmissions

Interference from downlink transmissions

Uplink data rate

Downlink data rate

D2D data rate

Inter-cell interference

Interference from D2D transmissions

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Constraints

    • SINR experienced by base station (uplink) must be acceptable

    • SINR experienced by cellular users (downlink) must be acceptable

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Constraints (contd.)

    • SINR experienced by D2D user (receiver) must be acceptable

    • Each uplink or downlink user must be uniquely assigned RBs. Orthogonality condition

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Constraints (contd.)

    • At most one D2D user and a cellular user (uplink or downlink) can share the same RB

    • Transmit power constraints

      • Uplink transmission

      • Downlink transmission

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Constraints (contd.)

    • Transmit power constraints (contd.)

      • D2D users

    • Power assignment constraints

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LTE – D2D Case Study

SELECTED TOPICS IN NETWORK DESIGN

Constraints (contd.)

    • Binary variable declaration for RB assignment

Observations

    • The given formulation is a mixed integer linear program
      • Linear constraints and linear objective
      • Binary and continuous variables

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Selected Topics in Network Design

Cloud radio access networks - CRAN

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

454 of 553

Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN – System model

  • Coverage is divided into cells with each macro cell having a base station referred to as radio resource head (RRH)
    • RRH performs ADC/DAC, power amplification and wireless transmission/reception
  • Baseband unit (BBU) corresponding to each macro cell is co-located in a cloud
    • BBU hierarchically sits on top of the RRHs
    • BBU performs signal processing operations
  • Distance between RRHs and BBUs can be up to 40 km

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Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN – System model (contd.)

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Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN – Architecture

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Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN versus LTE-A

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Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN Advantages

  • Smaller BBU pool is sufficient to manage large number of RRHs
  • Adaptability to non-uniform traffic
    • Higher statistical multiplexing gain can be achieved
  • Upgrading coverage and network capacity are simple
    • Ease in installing smaller RRH compared to bulky base station
    • Adding and reconfiguring centralized BBU pool is simple
    • Makes implementation of CoMP and D2D easier
    • Saves power and cost compared to traditional 4G networks

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Cloud radio access network - CRAN

SELECTED TOPICS IN NETWORK DESIGN

CRAN Challenges

  • Demarcating BBU and RRH functions
  • Addressing compatibility issues
  • Developing security mechanisms for centralized BBU pools
  • Data compression techniques for transport of IQ signals between BBU and RRH
  • Traffic engineering for backhaul network
  • Complex scheduling of BBUs and RRHs
  • Extending SDN and NFV concepts to C-RAN
  • Developing cooperative mechanisms in heterogeneous cells

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Selected Topics in Network Design

Hetnets and Fognets

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Hetnets – System model

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Hetnets – System model

  • Cooperation among the MBS and SBS leads to
    • Improving spectral efficiency and reducing power consumption of MBS
    • Better admission control and handoff management
    • Reducing deployment costs and operating costs
    • However, interference management among the different cells must be addressed

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Challenges to Hetnets design

    • Inter-cell interference mitigation
    • In-device self-interference cancellation
    • Dealing with unplanned deployment
    • Mobility management
    • Privately owned small cells
    • Performance analysis
    • Energy harvesting and utilization
    • Coordinated multipoint transmission

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Fognets – System model

    • Type of heterogeneous networks which are capable of supporting IoT applications, vehicular networks, etc.
    • Three tier architecture consisting of devices/end-users (bottom), fog nodes (middle) and cloud (top)
    • Fog nets offer low latency computing service
    • Resources allocated include radio resources and computing resources
    • End-users send their requests to fog nodes
    • Fog nodes can execute delay sensitive requests and offload the delay tolerant requests to cloud

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Fognets – System model

    • Type of heterogeneous networks which are capable of supporting IoT applications, vehicular networks, eyc.
    • Three tier architecture consisting of devices/end-users (bottom), fog nodes (middle) and cloud (top)
    • Fog nets offer low latency computing service
    • Resources allocated include radio resources and computing resources
    • End-users send their requests to fog nodes
    • Fog nodes can execute delay sensitive requests and offload the delay tolerant requests to cloud

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Hetnets and Fognets

SELECTED TOPICS IN NETWORK DESIGN

Fognets – Challenges

    • Resource allocation
    • Network formation
    • Security
    • Scalability and flexibility
    • Network protocols and overhead
    • QoS guarantees
    • Backhaul network design
    • Cooperation and control

467 of 553

Heterogeneous networks

SELECTED TOPICS IN NETWORK DESIGN

Case study – Downlink scheduling

    • Consider a heterogeneous network where the MBS and SBSs provide cellular communication and computing services. The users in a small cell can be served by either the MBS or the SBS whereas those outside the small cells are only served by the MBS. The small cells are non-overlapping with one another. Cellular transmissions are assigned orthogonal channels. Computing requests share cellular channels while guaranteeing minimum data requirement of all transmissions. Assume that radio resources are always sufficient.

468 of 553

Heterogeneous networks

SELECTED TOPICS IN NETWORK DESIGN

Case study – Downlink scheduling

    • Data
      • Set of requests; set of downlink users; set of channels; bandwidth of channels; maximum transmit power of MBS and SBSs; minimum data rate requirement; maximum service rate
    • Decisions
      • Number of requests served; assignment variables; transmit power of MBS and SBSs
    • Objective
      • To maximize sum data rate of all transmissions
    • Define constraints and formulate the problem

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Selected Topics in Network Design

Ad hoc networks

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

470 of 553

Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Ad hoc network versus infrastructure networks

  • Control / ownership / roles / topology / span / application / spectrum / scalability / link layer / network layer

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Wired versus wireless routing

  • Routing issues occur in MANETs and WSN
  • No routing issues in WPAN
  • Routing is optional in VANETs

Wired

Wireless

Shortest path exists

No shortest path

RIP

DSDV/AODV

Link cost based

Hop based

Less dynamic

Affected by mobility

Done by routers

Done by sensors/mobile devices

Centralized routing protocols

Distributed routing protocols

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Design concerns

  • Two main concerns are power and mobility
  • Techniques for physical layer to conserve power
    • Use of directional antenna
    • Controlling the transmission power with knowledge of neighbourhood.
  • Techniques for data-link layer to conserve power
    • Avoid unnecessary retransmissions.
    • Avoid collisions in channel access whenever possible.
    • Put receiver in standby mode whenever possible.
    • Use/allocate contiguous slots for transmission and reception whenever possible.
    • Turn radio off (sleep) when not transmitting or receiving.

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Design concerns

  • Techniques for network layer to conserve power
    • Consider route-relaying load
    • Consider battery life in route selection
    • Reduce frequency of sending control message.
    • Optimize size of control headers
    • Efficient route reconfiguration techniques
  • Techniques for transport layer to conserve power
    • Avoid repeated retransmissions
    • Handle packet loss in a localized manner
    • Use power-efficient error control schemes

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Ad hoc network – Types

  • Mobile ad hoc networks (MANETs)
  • Wireless sensor networks (WSNs)
  • Vehicular ad hoc networks (VANETs)
  • Personal area networks (PAN)
      • Bluetooth and Zigbee
  • Body area networks

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – ALOHA

    • Immediately transmit when a packet is generated
    • Users randomly wait before retransmission
    • Waiting time is an integral multiple of the transmission delay
    • How is the performance?

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – Slotted ALOHA

    • Time is divided into equal length slots
        • Slot length equals transmission delay
    • Users transmits at the start of a slot with probability p
    • If collision occurs then retransmit in the subsequent slots
    • Otherwise, transmission is considered success

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – Performance of ALOHA and slotted ALOHA

    • Let τf denote the average frame duration
    • Suppose the frames are transmitted at a rate of λ
    • Then average number of frames observed in a frame duration is λτf
      • Let G = λτf be referred to as the offered traffic
    • The throughput (denoted by S) is given by G×P0
      • Here P0 is probability that number of collisions is zero

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – Performance of ALOHA and slotted ALOHA

    • The throughput is then given by

    • The maximum throughput of ALOHA is given by

    • The maximum throughput of slotted ALOHA is given by

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – CSMA

  • A user wishing to transmit first listens to the medium
  • If the channel is in use, it must wait
  • If the medium is idle, it may transmit
  • If collision is detected, start binary exponential backoff
  • Types of CSMA: 1-persistent; Non-persistent; p-persistent

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – IEEE 802.11e for prioritized traffic

  • This standard is called IEEE 802.11e or EDCA
    • EDCA: Enhanced distributed coordinated access
  • 802.11e classifies the data types and assigns priorities
  • The MAC parameters are adapted according to the priorities
  • The operation is similar to IEEE 802.11 DCF except that there are different backoff window sizes and DIFS intervals (AIFS) for different traffic priorities
    • AIFS: Arbitration inter frame space
    • Lower the AIFS, higher the priority
    • Lower the CWmin, higher the priority

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Ad hoc networks

SELECTED TOPICS IN NETWORK DESIGN

Link layer protocols – IEEE 802.11e (contd.)

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Selected Topics in Network Design

MANETs : Part I

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

MANET – Introduction

  • Mobile ad hoc networks (MANETs) are also known as mesh networks
  • MANETs are local or metropolitan area networks
  • Nodes in MANET are mobile and communicate directly with adjacent nodes without the need for central controller
  • Topology of the MANET is dynamic
  • Examples of wireless mesh networks include:
    • An intra-home or inter-home wireless network
    • An enterprise-wide backbone wireless network of APs
    • Cellular mesh

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

MANET – Introduction

  • The characteristics of a mesh network are:
    • Grows organically
    • Does not necessarily require any “infrastructure”
    • Increases overall network capacity
    • Robust and resilient to faults
    • Self-managing and self-administering
    • Identity and security is a challenge

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

MANET – Introduction

  • The mobile nodes act as source, destination or relay
  • The mobile nodes forward packets for each other over possibly multihop routes
  • The capacity of the resulting end-to-end path directly depends on the efficiency of the routing protocol
  • Current research in MANETs is on efficient and scalable routing algorithms
  • Main routing challenges
    • Random network topology which can grow
    • Network connectivity due to wireless links and mobility of the users

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MANETs: Part I

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MANET routing protocols

  • Proactive (Table driven) – DSDV and WRP
    • Continuously update reachability information in the network
    • When a route is needed, it is immediately available
    • DSDV by Perkins and Bhagwat (SIGCOMM 94)
  • Reactive (Source driven) – DSR, AODV
    • Routing discovery is initiated only when needed
    • Route maintenance is needed to provide information about invalid routes
    • DSR by Johnson and Maltz
    • AODV by Perkins and Royer
  • Hybrid
    • Zone routing protocol (ZRP)

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

Dynamic Source Routing (DSR) protocol

  • In DSR, every node maintains a Route Cache when routing packets
  • Routes are assumed to be unidirectional
  • DSR divides the routing problem in two parts: Route Discovery and Route Maintenance

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

Dynamic Source Routing (DSR) protocol

  • Route Discovery involves exchange of RREQ and RREP packets along the path
  • Such packets contain the source address (initiator), destination address (target) and list of nodes traversed
  • RREQ packets also contain the request identifier
  • RREP packets have the list reversed

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MANETs: Part I

SELECTED TOPICS IN NETWORK DESIGN

Dynamic Source Routing (DSR) protocol

  • Route Maintenance involves detecting the link failures and notifying the error using ROUTE ERROR packet
  • Link failures can be detected using the following:
    • Link layer acknowledgements
    • Passive acknowledgements
    • Explicit hello or keep-alive messages

  • Basic version and enhanced versions:
    • Basic DSR involved entire list of traversed nodes to be sent in the packet headers
    • Enhanced versions used optimizations and flow labels
      • Example, packet salvaging was used

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Selected Topics in Network Design

MANETs : Part II

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

AODV (Ad hoc On-demand Distance Vector) protocol

  • Compared to DSR, AODV uses routing tables at nodes so that routes can be eliminated from the packets.
  • Routes are assumed to be bidirectional
  • AODV used sequence numbers to distinguish between old and new update route request messages
  • Route discovery is initiated when a node has packets for transmission
  • This route is maintained till completion of packet transmission or when destination is unreachable
  • Similar to DSR, the RREQ and RREP packets are involved in route discovery

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

AODV protocol – RREQ packets

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

AODV protocol – RREP packets

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

DSDV (Destination Sequenced Distance vector) protocol

  • DSDV routing is based on distance vector routing
      • Bellman Ford algorithm is used for updating the forwarding table
  • Every mobile node maintains a forwarding table
  • A forwarding table consist of possible destinations and number of hops to reach each destination
  • Each entry is marked by a sequence number assigned by the destination node
      • Sequence numbers help in avoiding routing loops
    • Forwarding table updates are periodically transmitted throughout the network to maintain consistency

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

DSDV (Destination Sequenced Distance vector) protocol

  • To prevent large overhead due to routing updates, two types of packets are transmitted
  • A full dump packet, carrying entire table, is transmitted occasionally
      • It requires multiple NPDUs
  • Smaller incremental packets are used to relay only changes since the last full dump
      • It requires one NPDU

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

DSDV (Destination Sequenced Distance vector) protocol

  • Nodes maintain additional table to store the data sent in incremental routing information packets
  • Besides a node should also relay data packets of neighbors
  • New broadcasts contain the following
      • Address of the destination
      • Number of hops to reach the destination
      • Sequence number of the broadcast received from the destination
      • The route with recent sequence number is always used

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MANETs: Part II

SELECTED TOPICS IN NETWORK DESIGN

DSDV (Destination Sequenced Distance vector) protocol

  • Nodes also maintain settling time of the routes or weighted average time that routes to a destination fluctuate before the route with the best metric is received
  • By delaying the broadcast of a routing update by the length of the settling time, mobile users can reduce the network traffic

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Selected Topics in Network Design

MANETs : Part III

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

WRP – Wireless Routing Protocol

  • Wireless routing protocol (WRP) is also table driven routing protocol
  • Four types of tables are maintained
      • Distance table
      • Routing table
      • Link cost table
      • Message retransmission list (MRL) table

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

WRP – Wireless Routing Protocol

  • Each entry of the MRL table contains the following
    • Sequence number of the update message
    • Retransmission counter
    • Acknowledgement-required flag vector with one entry per neighbor
    • List of updates sent in update message
  • MRL records which updates in the update message should be retransmitted and which neighbor should acknowledge the retransmission
  • Mobiles update their neighbors of link changes using update messages

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

WRP – Wireless Routing Protocol

  • An update message contains the following
      • List of updates (destination, distance to destination and predecessor of destination)
      • List of responses indicating which member should acknowledge the update
  • Upon receiving an update, a neighbor node updates its distance table and checks for new paths through other nodes
      • Any new paths are relayed back to the original node
  • Nodes learn presence of neighbors using ACK or periodic hello messages

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

WRP – Wireless Routing Protocol

  • When a hello message from a new node is received, the routing table is updated and a copy of the routing table is replied
  • In WRP, routing nodes exchange distance to destination and second-to-last-hop information of each destination
      • This solves looping and count-to-infinity problems due to link failure

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

Summary of routing protocols – Design requirements

  • Must be scalable
  • Must be fully distributed, no central coordination
  • Must be adaptive to topology changes caused by movement of nodes
  • Route computation and maintenance must involve a minimum number of nodes
  • Must be localized, global exchange involves a huge overhead
  • Must be loop-free
  • Must converge to optimal routes very fast
  • Must optimally use the scare resources: bandwidth, battery power, memory, computing
  • Should provide QoS guarantees

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

Pros and cons of proactive routing protocols

  • Advantages: low delay of route setup process; all routes are immediately available
  • Disadvantages: high bandwidth requirements; updates due to link loss leads to high control overhead; low scalability; control overhead is proportional to the number of nodes; high storage requirements; whole table must be in memory

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MANETs: Part III

SELECTED TOPICS IN NETWORK DESIGN

Pros and cons of reactive routing protocols

  • Advantages: routes are established on-demand; small control overhead; low storage requirements; only needed routes are in cache
  • Disadvantages: low scalability; no route updates at other times; high delay of route setup process;

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Selected Topics in Network Design

WSN – Introduction

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Components and roles

  • WSN comprises of a large number of disposable sensors deployed to sense and report ambient conditions about the surrounding environment
  • WSNs are deployed in applications that require unattended operations
  • The sensors can communicate either among each other or directly to an external base station
  • A greater number of sensors allows for sensing over larger geographical regions with greater accuracy
  • Sensor nodes are prone to failures

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Components and roles

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Components and roles

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Inside a sensor node

  • Sensor nodes are limited in power, computational capacities, and memory

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

Sensor node – Design factors

  • Production costs: The cost of each sensor node should be much less than US $1 in order for the sensor network to be feasible.
  • Transmission media: In a multi-hop sensor network, communicating nodes are linked by radio, infrared or optical media.
  • Environment: Sensor network usually work unattended in remote geographic areas, such as large machinery, ocean, biologically and chemically contaminated field.

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

WSN design issues

  • Node deployment
  • Energy consumption without losing accuracy
  • Data reporting
  • Coverage
  • QoS

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

WSN Applications

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

WSN Applications

    • Target field imaging
    • Intrusion detection
    • Weather monitoring
    • Security and tactical surveillance
    • Distributed computing
    • Detecting ambient conditions such as temperature, movement, sound, light, or the presence of certain objects
    • Inventory control
    • Disaster management

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

WSN routing issues

    • Link access can be performed by Zigbee or Bluetooth or other random access techniques
    • Routing is affected by the failure of sensors, energy consumption and mobility (if sensors are mobile)
    • The energy consumption in WSN can be improved by
      • Data aggregation and in-network processing
      • Clustering with different node role assignments
      • Data-centric methods

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Wireless sensor networks - Introduction

SELECTED TOPICS IN NETWORK DESIGN

WSN routing protocols

  • Classification based on network structure:
    • Flat, hierarchical or location-based
  • Classification based protocol operation:
    • Multipath-based, query-based, negotiation-based, QoS-based, and coherent-based

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Selected Topics in Network Design

WSN – Routing protocols

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Flat Routing

  • Each node typically plays the same role and sensor nodes collaborate together to perform the sensing task
  • Due to the large number of such nodes, it is not feasible to assign a global identifier to each node
  • BS sends queries to certain regions and waits for data from the sensors located in the selected regions
  • Since data is being requested through queries, attribute-based naming is necessary to specify the properties of data
  • Examples: Sensor protocols for information via negotiation (SPIN), directed diffusion (DD), energy aware routing (EAR).

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – SPIN

  • Data is described by meta-message (ADV).
  • Send ADV to neighbors.
  • If neighbor do not have the data, sends REQ; otherwise, do nothing.
  • As the REQ received by sender, then it sends the data to the neighbor.

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – SPIN (contd.)

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – SPIN (contd.)

  • Advantage: Each node only needs to know its one-hop neighbors.
  • Disadvantage: Data advertisement cannot guarantee the delivery of data.

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – DD

  • The idea aims at diffusing data through sensor nodes by using a naming scheme for the data.
  • DD suggests the use of attribute-value pairs for the data and queries the sensors in an on demand basis
  • To create a query, an interest is defined using a list of attribute-value pairs such as name of objects, interval, duration, geographical area, etc.
  • The interest is broadcast by the sink and propagated to neighboring nodes
  • Neighboring nodes reply with gradient containing data rate, duration and expiration time derived from the received interest’s fields

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – DD (contd.)

Comparison of DD and SPIN

  • In Directed Diffusion the sink queries the sensor nodes if a specific data is available by flooding some tasks.
  • In SPIN, sensors advertise the availability of data allowing interested nodes to query that data.

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Selected Topics in Network Design

WSN – Routing protocols

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – Hierarchical Routing

  • Scalability is one of the major design attributes of sensor networks
  • Higher sensor density leads to higher latency and lower tracking
  • To achieve load balancing and improve network lifetime, clustering of nodes and forming hierarchy is important
  • Data aggregation and fusion decrease the number of transmitted messages
  • Cluster formation is typically based on the energy reserve of sensors and sensors proximity to the cluster head

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – LEACH

  • Low-energy adaptive clustering hierarchy is hierarchical routing protocol
  • Let p denote the desired % of nodes which can become cluster heads out of G nodes
  • Let r denote the current round
  • Any node n out of G selects a random number between 0 and 1
  • The node becomes a cluster head if the chosen random number was greater than threshold T(n)

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – LEACH (contd.)

  • After becoming cluster head, the node broadcasts an advertisement
  • Based on the received signal strength, other nodes select and reply to the advertisement, thus becoming cluster members
  • Following this the cluster head creates a TDMA schedule and assigns each node a time slot to transmit
  • This transmit schedule is broadcast to the cluster members
  • Cluster members transmit according to the schedule to the cluster head

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – LEACH (contd.)

  • The cluster head uses CDMA in each slot to avoid inter-cluster interference
  • The cluster head periodically aggregates the data collected and transmits to the sink
  • After a fixed interval, the cluster head relinquishes its position

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – TEEN

  • Threshold sensitive Energy Efficient sensor Network protocol is hierarchical and reactive to critical events.
  • Base station defines cluster heads, transmission schedule and thresholds for reporting of information.
  • The sensors can decide whether to report the information by comparing with the thresholds
  • Cluster heads perform data aggregation to save energy

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Wireless sensor network – TEEN (contd.)

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Wireless sensor networks – Routing protocols

SELECTED TOPICS IN NETWORK DESIGN

Comparison of flat versus hierarchical routing

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Selected Topics in Network Design

Bluetooth

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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WPAN

SELECTED TOPICS IN NETWORK DESIGN

Wireless personal area network

  • A personal area network (PAN) is an interconnection of devices for personal use in the range of 1-10 m
  • WPAN technologies: Bluetooth, Zigbee, wireless USB, IrDA
  • Operates in ISM band
  • Standards provide architecture, PHY and MAC
  • IEEE 802.15 working group

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

PHY Specifications

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

Usage models

    • File transfer: Transfer of directories, folders, files and browsing options for user
    • Internet bridge: Provide dial-up networking and PPP service over RFCOMM
    • LAN access: Connects devices on piconet to LAN
    • Synchronization: Device to device synchronization such as phonebook, calendar, messages, etc.
    • Three-in-one phone: Telephone handsets can perform as cordless telephone, intercom and as cellular phone
    • Headset: Remote device's audio input and output interface

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

Network architecture

    • Piconet Scatternet

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

Protocol stack

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

Frame format

  • DAC – Device access code
  • CAC – Channel access code
  • IAC – Inquiry access code

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Bluetooth

SELECTED TOPICS IN NETWORK DESIGN

Baseband states entered by Bluetooth devices

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Selected Topics in Network Design

VANETs

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

Introduction

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

Applications

    • Active road safety applications
    • Traffic efficiency and management applications
    • Infotainment applications
    • More generally
    • Vehicle positioning, Automated toll collection, Parking lot payment, Cargo tracking, Road condition warning, Traffic information, Intersection collision warning, Traffic accident warning, Abnormal vehicle condition warning, Weather information, Advertisements, etc.

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

PHY specifications

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

WAVE protocols

Wireless Access in Vehicular Environments

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

WAVE operation

    • DSRC: 1 CCH, 6 SCH (1 public safety, 1 vehicle safety, 4 data channels)
    • WAVE advertisement: WBSS identifier, availability of a service, selected SCH, synchronization timing information

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VANETs

SELECTED TOPICS IN NETWORK DESIGN

VANET challenges

  • Addressing and Geographical addressing
  • Risk analysis and management
  • Data-centric Trust and Verification
  • Anonymity, Privacy and Liability
  • Secure Localization
  • Forwarding algorithms
  • Delay constraints
  • Prioritization of data packets and congestion control
  • Reliability and cross-layering between transport and network layers

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Selected Topics in Network Design

IoT applications

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering

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IoT and Its Applications

SELECTED TOPICS IN NETWORK DESIGN

IoT – Introduction

  • Internet of things (IoT) extends the traditional interaction between applications to interaction between “anything”
  • Examples of IoT: Industrial systems, smart grid, drones flight control, connected cars, trains, surveillance cameras, actuators, medical devices, etc.
  • Challenges for IoT: Stringent latency, network bandwidth, resource constrained devices, security, cyber-physical systems, fairness, privacy, energy efficiency, routing, etc.

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IoT and Its Applications

SELECTED TOPICS IN NETWORK DESIGN

Fog computing – Introduction

  • Fog or edge computing is the seen as a promising solution to address the challenges of IoT
    • 5G communication is expected to enhance the deployment of the IoT and Fog technologies
  • Examples of fog devices: access routers, edge servers, micro-datacenters, tablets, smart phones, wearable devices, TV set-boxes, smart meters, etc.
  • Fog nodes have limited computing ability and storage
  • Fog nodes are widely deployed (e.g., cellular networks, smart homes, smart buildings, road traffic, etc.)
  • Fog nodes are heterogeneous

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IoT and Its Applications

SELECTED TOPICS IN NETWORK DESIGN

Fog network architecture and operation

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IoT and Its Applications

SELECTED TOPICS IN NETWORK DESIGN

Challenges to fog networks

  • Fog nodes are heterogeneous
  • Computation offloading decisions
  • Load balancing
  • Fog control may be challenging
  • New routing protocols
  • Energy versus latency dilemma
  • Reliability versus latency dilemma
  • Overhead versus latency dilemma

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IoT and Its Applications

SELECTED TOPICS IN NETWORK DESIGN

Case study: Industrial IoT

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vamsikrishnatumuluru@pes.edu

+91 80 26721983 Extn 766

THANK YOU

Vamsi Krishna Tumuluru

Department of Electronics and Comm. Engineering