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A Meta-Learning Approach for Energy-Efficient Resource Allocation and Antenna Selection in STAR-BD-RIS Aided Wireless Networks

Farhadi, Armin; Hatami, Roya; Mili, Mohammad Robat; Masouros, Christos; Bennis, Mehdi; (2025) A Meta-Learning Approach for Energy-Efficient Resource Allocation and Antenna Selection in STAR-BD-RIS Aided Wireless Networks. IEEE Wireless Communications Letters 10.1109/LWC.2025.3543780. (In press). Green open access

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Abstract

This paper focuses on a wireless network that utilizes beyond diagonal reconfigurable intelligent surfaces (BD-RIS). In this network, multiple BD-RISs assist a multi-antenna base station (BS) with two sectors that simultaneously transmit and reflect signals to single-antenna users. The goal is to maximize energy efficiency by jointly optimizing beamforming at the BS, the BD-RISs’ matrix, and antenna selection under the maximum power budget at the BS, BD-RISs’ matrix, and antenna selection constraints. The formulated problem is non-convex and challenging to be solved optimally. To address this difficulty, we propose a meta-soft actor critic (Meta-SAC) algorithm, which enables the BS to adjust its beamforming capabilities and BD-RISs’ matrix and assign antennas to users. Simulation results demonstrate the superiority of Meta-SAC in comparison with other meta algorithms and a reasonable response compared to the convex optimization benchmark. We also study the influence of system model parameters on the objective function of the proposed optimization problem. In addition, the results show that the multi-BD-RIS system reaches a higher energy efficiency and data rate compared to the provided benchmarks.

Type: Article
Title: A Meta-Learning Approach for Energy-Efficient Resource Allocation and Antenna Selection in STAR-BD-RIS Aided Wireless Networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/LWC.2025.3543780
Publisher version: https://doi.org/10.1109/LWC.2025.3543780
Language: English
Additional information: This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Antennas, Reconfigurable intelligent surfaces, Metalearning,Energy efficiency, Optimization, Electronic mail,Computer architecture, Array signal processing, Reflection, Impedance
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10205546
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