An Efficient Convex-Hull Relaxation Based Algorithm for Multi-User Discrete Passive Beamforming

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Bibliographic Details
Main Authors:	Lai, Wenhai, Wu, Zheyu, Feng, Yi, Shen, Kaiming, Liu, Ya-Feng
Format:	Preprint
Published:	2024
Subjects:	Information Theory Signal Processing
Online Access:	Acceder al recurso
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author	Lai, Wenhai Wu, Zheyu Feng, Yi Shen, Kaiming Liu, Ya-Feng
author_facet	Lai, Wenhai Wu, Zheyu Feng, Yi Shen, Kaiming Liu, Ya-Feng
contents	Intelligent reflecting surface (IRS) is an emerging technology to enhance spatial multiplexing in wireless networks. This letter considers the discrete passive beamforming design for IRS in order to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among multiple users in an IRS-assisted downlink network. The main design difficulty lies in the discrete phase-shift constraint. Differing from most existing works, this letter advocates a convex-hull relaxation of the discrete constraints which leads to a continuous reformulated problem equivalent to the original discrete problem. This letter further proposes an efficient alternating projection/proximal gradient descent and ascent algorithm for solving the reformulated problem. Simulation results show that the proposed algorithm outperforms the state-of-the-art methods significantly.
format	Preprint
id	arxiv_https___arxiv_org_abs_2407_20914
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	An Efficient Convex-Hull Relaxation Based Algorithm for Multi-User Discrete Passive Beamforming Lai, Wenhai Wu, Zheyu Feng, Yi Shen, Kaiming Liu, Ya-Feng Information Theory Signal Processing Intelligent reflecting surface (IRS) is an emerging technology to enhance spatial multiplexing in wireless networks. This letter considers the discrete passive beamforming design for IRS in order to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among multiple users in an IRS-assisted downlink network. The main design difficulty lies in the discrete phase-shift constraint. Differing from most existing works, this letter advocates a convex-hull relaxation of the discrete constraints which leads to a continuous reformulated problem equivalent to the original discrete problem. This letter further proposes an efficient alternating projection/proximal gradient descent and ascent algorithm for solving the reformulated problem. Simulation results show that the proposed algorithm outperforms the state-of-the-art methods significantly.
title	An Efficient Convex-Hull Relaxation Based Algorithm for Multi-User Discrete Passive Beamforming
topic	Information Theory Signal Processing
url	https://arxiv.org/abs/2407.20914

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