EN_EP012M71_SALZENSTEIN_Communications numériques

DIGITAL COMMUNICATIONS

Main lecturer

Mail address

Phone number

Fabien SALZENSTEIN

Other lecturer(s)

APOGEE code

Track - Year - Option - Semester

Coefficient = ECTS

Duration

EP012M71

Engineer - 2Y G I2S / 2Y IR RIO - S8

Master - 1Y ASI G + HCI - S2

2 / 2.50

7h CM, 12,25h CI, 5,25h TD

EXAMS

Duration

Authorized documents

If yes, which ones :

School calculator authorized

Session 1

7 CI sessions (Ch Collet) followed by 4 course sessions and + 3 TD sessions (F Salzenstein + monitor)

Yes

A4 double sided sheet

Yes

Session 2

to complete

Yes / No

	Prerequisites Introduction to signal processing: deterministic analog signals.
	Lecture goals We present here the principles of digital telecommunications, assuming prior knowledge of the basic signal theory. The main purpose deals with the understanding of the different elements and principles that enable a high-performance remote communication, reliable and robust. An important part of this course (about 40%) uses the Matlab tool (Signal Processing and Communications toolboxes) by simulating a transmission of a text message and an audio signal.
	Detailed outline This course provides an illustration of the contribution of the signal theory in the context of the transmission of information. It has one of the essential applications that can address the signal theory: telecommunications are a main piece of our information societies. We introduce the basic concepts describing the structure of a transmission system: digitization, online codes, source coding, cryptography, channel coding, transmitter, transmission channel, structure of the receiver. We briefly describe the techniques allowing a signal to the transmit by a baseband or after modulation depending on the context. The notions of inter-symbol interference will be presented, in order to investigate the optimum waveform to be issued to solve it. The optimal receiver structure will be addressed by introducing the necessary concepts such as decision theory. Notions such as source coding techniques, channel coding (parity codes, convolutional codes, cyclic codes) and cryptography will be explained and illustrated by the means of the fundamentals of information theory (entropy, mutual information, channel capacity), which will be a subject of a detailed presentation.
	Applications (TP MatLab) TP1. Communication via baseband and carrier frequency; various models of the transmission channel will be treated: with infinite or finite bandwidth channel, non noisy or noisy. TP2. Source coding: transmission of a text, ASCII code, Huffman encoding, Morse code. Compression of a digital image by the JPEG format; TP3. Channel coding: parity codes, Hamming code, convolutional code;
	Acquired skills Basic techniques of visualization and digital signal processing using MatLab. Digitizing an analog signal, modulation techniques for transmission of digital information. Understanding of key modules required for encoding and transmit the digitalized information: channel coding and source, channel capacity and theory of information. Understanding of the criteria used in decision theory. Knowing how to solve basic problems of information transmission in digital form by rapidly identifying modules that can be optimized. Understanding the techniques used in text, audio and video compression.