Joint Beamforming and Power Allocation Design for Stacked Intelligent Metasurfaces-Aided Cell-Free Massive MIMO Systems

Stacked intelligent metasurfaces (SIM) is considered a revolutionary technology that enables powerful signal processing directly in the electromagnetic (EM) wave domain and has significant energy-saving advantages. In this work, we explore the performance of a SIM-aided cell-free massive multiple-input multiple-output (CF-mMIMO) system that incorporates joint beamforming and power allocation. Specifically, we jointly design the transmit power allocation at access points (APs) and the wave-based beamforming at SIMs for maximizing the system sum rate. An alternating optimization (AO)-based iterative algorithm is proposed for solving the complex non-convex problem, which is decomposed into two subproblems. For the transmit power allocation subproblem, maximum ratio transmission (MRT) is employed to maximize signal receiving power. For the optimization subproblem of SIM phase shifts, a proficient gradient ascent algorithm is deployed to ensure convergence to a local optimum. Simulation results show an enhancement in the performance of the proposed AO algorithm compared to baseline methods. Additionally, numerical results contrast with those of RIS-aided CF-mMIMO systems, highlighting the advantages of SIMs in CF networks and demonstrating the efficacy of SIM-enabled wave-based beamforming design, where increasing the number of meta-atoms and layers of SIMs is beneficial for improving the sum rate.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-11-18
DOI
https://doi.org/10.1109/tvt.2024.3499968
Citations
18
Primary Topic
Antenna Design and Analysis
Type
article
Field-Weighted Citation Impact
23.38
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article

Joint Beamforming and Power Allocation Design for Stacked Intelligent Metasurfaces-Aided Cell-Free Massive MIMO Systems

Enyu Shi, Jiancheng An, Chau Yuen, Yu Wei Lu et al.
18 citations
IEEE Transactions on Vehicular Technology
Antenna Design and Analysis
23.38
article

Joint Beamforming and Power Allocation Design for Stacked Intelligent Metasurfaces-Aided Cell-Free Massive MIMO Systems

Enyu Shi, Jiancheng An, Chau Yuen, Yu Wei Lu, Bo Ai, Jiayi Zhang, Yating Hu
article en
18 citations

Abstract

Stacked intelligent metasurfaces (SIM) is considered a revolutionary technology that enables powerful signal processing directly in the electromagnetic (EM) wave domain and has significant energy-saving advantages. In this work, we explore the performance of a SIM-aided cell-free massive multiple-input multiple-output (CF-mMIMO) system that incorporates joint beamforming and power allocation. Specifically, we jointly design the transmit power allocation at access points (APs) and the wave-based beamforming at SIMs for maximizing the system sum rate. An alternating optimization (AO)-based iterative algorithm is proposed for solving the complex non-convex problem, which is decomposed into two subproblems. For the transmit power allocation subproblem, maximum ratio transmission (MRT) is employed to maximize signal receiving power. For the optimization subproblem of SIM phase shifts, a proficient gradient ascent algorithm is deployed to ensure convergence to a local optimum. Simulation results show an enhancement in the performance of the proposed AO algorithm compared to baseline methods. Additionally, numerical results contrast with those of RIS-aided CF-mMIMO systems, highlighting the advantages of SIMs in CF networks and demonstrating the efficacy of SIM-enabled wave-based beamforming design, where increasing the number of meta-atoms and layers of SIMs is beneficial for improving the sum rate.

IEEE Transactions on Vehicular TechnologyVol. 74(3)
Nanyang Technological University (SG), Beijing Jiaotong University (CN)
Openalex Percentile: Top 1%
Antenna Design and Analysis
23.38
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Joint Beamforming and Power Allocation Design for Stacked Intelligent Metasurfaces-Aided Cell-Free Massive MIMO Systems — Enyu Shi, Jiancheng An, et al. · IEEE Transactions on Vehicular Technology (2024) | TGRS Research Map | TGRS