Multi-user beamforming and transmission based on intelligent reflecting surface

Liu, Y., Zhang, L. and Imran, M. A. (2022) Multi-user beamforming and transmission based on intelligent reflecting surface. IEEE Transactions on Wireless Communications, 21(9), pp. 7329-7342. (doi: 10.1109/TWC.2022.3157808)

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Intelligent Reflecting Surfaces (IRS) show a revolutionary potential for wireless communications. In this paper, a single IRS is used to achieve distributed multi-user beamforming and interference-free transmission. We first establish the IRS assisted multi-user system model and formulate an optimization problem called multi-user linearly constrained minimum variance (MU-LCMV) beamformer, under the criterion of minimizing the overall received signal power subject to a certain level of power response (e.g., unit power response) at desired signal directions and arbitrary low power response (e.g., zero power response) at the interference directions. A closed-form amplitude-unconstrained phase-continuous (AUPC) solution is derived first, then an amplitude-constrained phase-continuous (ACPC) solution is obtained by using sequential quadratic programming (SQP). Given the solutions, the IRS beam pattern shows that to achieve multi-user (N pairs of transceivers, N > 1) transmission through a single surface, up to N - 1 redundant beams are generated, significantly affecting power efficiency. The directions of the redundant beams are mathematically derived. The effect of mutual coupling on IRS is also analyzed to show the characteristic of side lobes. Simulation results verify the existence and accuracy of the redundant beam directions. This work can potentially enhance state-of-the-art wireless communication systems ranging from transceiver design, system and architecture design, network deployment and self-organizing-network operations.

Item Type:Articles
Additional Information:This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Projects EP/V519686/1 and EP/S02476X/1.
Glasgow Author(s) Enlighten ID:Zhang, Professor Lei and Imran, Professor Muhammad
Authors: Liu, Y., Zhang, L., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:IEEE Transactions on Wireless Communications
ISSN (Online):1558-2248
Published Online:15 March 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in IEEE Transactions on Wireless Communications 21(9): 7329-7342
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
304481Resource Orchestration for Diverse Radio SystemsLei ZhangEngineering and Physical Sciences Research Council (EPSRC)EP/S02476X/1ENG - Systems Power & Energy