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Abstract

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• The forthcoming 6G wireless communication technologies are anticipated to be portable and offer inherent security, massive spectral bandwidth, widespread coverage, and fast data rates.
• Energy-efficient communication is fundamental to these wireless technologies.
• Distributed beamforming is a possible candidate to achieve this goal, in which various controllable electromagnetic wave parameters are tuned to enhance the efficiency of wireless data and energy transfer.
• In this work, we first demonstrate that the distributed beamforming technique enhances the power transfer efficiencies in two-hop energy transfer applications.
• Additionally, we show that if beamforming is ensured in a two-ray channel model then it may improve received power thereby allowing energy-efficient communication. However, since non-line of sight link cannot act as an independent source it forms part of a passive beamforming scenario.
• After demonstrating the performance results of the beamforming technique, our next sequence of work presents the methodology to achieve energy-efficient distributed beamforming using orthogonal transmissions.
• In this work, we first propose a Rx-DBF algorithm, for information transfer without receiver feedback. It is proven to achieve near-perfect beamforming gain and is channel fading agnostic. Exploiting the correlation in beamformed output, a sporadic receiver feedback scheme is also introduced, which prolongs the duration of beamforming gain to aid information or power transfer.
• The proposed schemes in receiver-end distributed beamforming are demonstrated to be more energy efficient compared to the closest competitive approaches in the literature.

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Introduction

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Distributed Beamforming System Model

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References

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1. D. Mishra and S. De, "Optimal Relay Placement in Two-Hop RF Energy Transfer," in IEEE Trans. Commun., vol. 63, no. 5, pp. 1635-1647, May 2015.
2. S. Kumar, S. De and D. Mishra, "RF Energy Transfer Channel Models for Sustainable IoT," in IEEE Internet Things J., vol. 5, no. 4, pp. 2817-2828, Aug. 2018.
3. S. Sachdev and S. De, "Energy Efficient Receiver-End Distributed Beamforming Using Orthogonal Transmissions," in IEEE Commun. Lett., vol. 26, no. 7, pp. 1648-1652, July 2022.
4. P. Sriploy and M. Uthansakul, “Nonfeedback distributed beamforming using spatial-temporal extraction,” Int. J. Antennas Propag., vol. 2016, pp. 1–16, Jan. 2016.

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Acknowledgement

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This work is supported by DoT grant 4-23/5G test bed/2017-NT, DST-SERB grant CRG/2019/002293 and Abdul Kalam Technology Innovation National Fellowship.

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Conclusions

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• In this work, we discussed the various beamforming strategies proposed in different applications for enhanced communication and energy transfer.
• We provided profound details on distributed beamforming and application-specific execution challenges.
• We presented DBF for enhancing RFET efficiency in 2HET, wherein the relay node in itself acts as an independent transmitter. The work proposed to optimize the relay node location to obtain phase synchronicity at the receiver.
• We developed a practical path loss model for RFET by incorporating the NLOS component due to ground reflection and proposed the realization of passive beamforming for receive power enhancement.
• We proposed an energy-efficient receiver-end beamforming technique for phase synchronization of the independent nodes involved in communication.
• The proposed receiver-end distributed beamforming can be incorporated in both data and energy transfer applications and is agnostic to channel fading scenarios. It has been shown to be more efficient compared to the closest competitive approach in literature.
• The small broadcast feedback allows the achievement of beamforming gains for consecutive slots, without feedback or receiver processing, thereby allowing high data rate information transfer and quick charging.
• Distributed beamforming does not compromise with the safety aspects during data or energy transfer, in fact additionally offers beamforming gains.

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Our current work and future scope

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• Currently, working to cover different fading scenarios by considering a generalized channel model and exploiting the channel distribution for reduced processing in phase synchronization.
• Additionally, working on distributed beamforming methods that take channel correlations into account for sustained beamforming thereby reducing the feedback requirements.
• Also, exploring the impact of polarization on distributed beamforming.
• In the future, we intend to harvest the ambient RF and optical beams by incorporating distributed beamforming thereby improving harvesting efficiencies.

Electrical Engineering

Distributed Beamforming Based Wireless Communication and Energy Transfer

Srishti Sharma, Smriti Sachdev and Swades De*

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Industry Day Theme

# Communication Technologies (CT)

Various Beamforming Scenarios and Strategies

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This section includes the sequence of our works proposed on beamforming. Application-based system models and the corresponding performance results are shown in their particular subsection.

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Fig. 12. Optimum efficiency comparison and verification with end-to-end hardware experiments

Fig. 17. Average and worst case beamforming gain with the proposed Rx-DBF

Fig. 16. Prolonged beamformed transmission in sporadic feedback.  

Fig. 15. Rx-DBF: Orthogonal transmission (OT) stage followed by beamforming (BF) stage.

Fig. 2. An example application of distributed beamforming: range extension.

Fig. 18. Effect of fast fading on DBF gain, with N=2.

Fig. 20. Energy consumption in synchronization with the proposed methods.

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• Rx-DBF: It is an efficient method proposed for information transfer through DBF using one transmission per transmitter and no receiver feedback. In this method, beamforming is performed at the baseband level using receiver-end algorithm in which the transmitter’s signal is shifted with a selected step size to find an optimum phase correction that results in maximum combined signal strength.
• Sporadic receiver feedback scheme: This method is presented for sustained beamforming over extended periods by tracking beamformed output. After the optimum phase shifts have been derived using Rx-DBF, the receiver feeds them back to the transmitters in one broadcast transmission. The transmitters then transmit in phase synchronous mode and beamforming is directly achieved at the receiver. This beamforming is sustained till fall in beamforming gain is detected by the receiver due to changing channel conditions.

• DBF can be energy intensive due to several coordinating communications among the collaborating nodes. The objective of the proposed methods is to achieve energy-efficient DBF for information or power transfer between energy-constrained wireless nodes.
• Depending on the stage of the proposed method, the transmitters transmit in either orthogonal mode or phase synchronous mode.
• In orthogonal mode transmitters can send the common message using only orthogonal resource. The receiver computes phase corrections for achieving beamforming based on a single transmission from each transmitter.
• Once phase corrections are fed back, the transmitters use phase synchronous mode with simultaneous transmissions to achieve direct beamforming at the receiver for extended duration.
• This work proposes two methods for achieving the beamformed output:

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Fig. 14. System model for proposed orthogonal transmissions based distributed beamforming.

Fig. 9. Proposed channel model for incorporating the effect of NLOS component in RF energy transfer.

Beamforming in two-ray channel model for RFET [2]

Energy-efficient receiver-end distributed beamforming [3]

• If the relay node transmits the harvested RF energy, then closer to the RF source may be a better position for the relay node.
• However, if the harvesting part is neglected and the relay is assumed to be capable of continuous transmission at the target node, then to maximize the received power, a position closer to the target node is more suited as it suffers from lesser path loss.

• Fig. 3 shows the network topology for 2HET. Transmission from the relay node is discontinuous, because the energy relay node does not have a dedicated energy supply. Thus, there is a continuous cycle of transmission (ON or active) state and no transmission (OFF) state in the relay node. As the relay node has two separate antennas - one for the reception of RF energy and the other for its transmission, it can continuously harvest energy from the RF source, though it transmits in bursts only during the ON state.
• In this work, an optimization algorithm is proposed for optimal relay placement (ORP) in 2HET. The inclusion of DBF reduces the ORP problem from 2D to 1D.
• Additionally, distributed beamforming offers improved 2HET efficiency with faster convergence to optimal relay problem solutions.
• Tradeoff at the Relay: Scavenged versus delivered energy

Optimal relay placement with distributed beamforming in two-hop energy transfer (2HET) [1]