Power-Aware Sparse Reflect Beamforming in Active RIS-Aided Interference Channels

In this article, we are interested in active reconfigurable intelligent surface (RIS)-aided interference channels in which K user pairs share the same time and frequency resources with the aid of active RIS. Thanks to the promising amplitude amplification capability, activating a moderate number of reflecting elements (REs) rather than all of them is sufficient for the active RIS to mitigate the cross-channel interferences. Motivated by this, we propose a power-aware sparse reflect beamforming (SRB) design for the active RIS-aided interference channels, which allows the active RIS to flexibly adjust the number of activated REs for the sake of reducing power costs. Specifically, we establish the power consumption model in which only those activated REs consume the biasing and operation power that supports the amplitude amplification, yielding an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm power consumption function. Based on the proposed model, we investigate a sum-rate maximization problem and an active RIS power minimization problem by carefully designing the SRB vector. To solve these problems, we first replace the nonconvex <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm function with an iterative reweighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm function. Subsequently, we employ fractional programming to solve the sum-rate maximization and utilize semidefinite programming combined with the difference-of-convex algorithm (DCA) to address the active RIS power minimization both of which are proven to converge well. Numerical results show that the proposed sparse designs can notably increase the sum rate of user pairs and decrease the power consumption of the active RIS in interference channels.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-08-13
DOI
https://doi.org/10.1109/jiot.2024.3443173
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Power-Aware Sparse Reflect Beamforming in Active RIS-Aided Interference Channels

Ying‐Chang Liang, Ruizhe Long, Hu Zhou
IEEE Internet of Things Journal
Advanced MIMO Systems Optimization
article

Power-Aware Sparse Reflect Beamforming in Active RIS-Aided Interference Channels

Ying‐Chang Liang, Ruizhe Long, Hu Zhou
article en

Abstract

In this article, we are interested in active reconfigurable intelligent surface (RIS)-aided interference channels in which K user pairs share the same time and frequency resources with the aid of active RIS. Thanks to the promising amplitude amplification capability, activating a moderate number of reflecting elements (REs) rather than all of them is sufficient for the active RIS to mitigate the cross-channel interferences. Motivated by this, we propose a power-aware sparse reflect beamforming (SRB) design for the active RIS-aided interference channels, which allows the active RIS to flexibly adjust the number of activated REs for the sake of reducing power costs. Specifically, we establish the power consumption model in which only those activated REs consume the biasing and operation power that supports the amplitude amplification, yielding an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm power consumption function. Based on the proposed model, we investigate a sum-rate maximization problem and an active RIS power minimization problem by carefully designing the SRB vector. To solve these problems, we first replace the nonconvex <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm function with an iterative reweighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm function. Subsequently, we employ fractional programming to solve the sum-rate maximization and utilize semidefinite programming combined with the difference-of-convex algorithm (DCA) to address the active RIS power minimization both of which are proven to converge well. Numerical results show that the proposed sparse designs can notably increase the sum rate of user pairs and decrease the power consumption of the active RIS in interference channels.

IEEE Internet of Things JournalVol. 11(22)
University of Electronic Science and Technology of China (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Project 211, Fundamental Research Funds for the Central Universities, Key Research and Development Program of Sichuan Province
Affordable and clean energy
Openalex Percentile: Top 90%
Advanced MIMO Systems Optimization
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