Joint optimization of deployment and topology for irregular RIS in wireless communication systems.

Abstract

This paper considers an irregular reconfigurable intelligent surface (IRIS)-aided multi-user wireless communication system. A novel block alternating optimization (BAO) algorithm framework is proposed to maximize the system’s weighted sum-rate (WSR) by jointly optimizing base station (BS) active beamforming, IRIS deployment, IRIS passive beamforming and IRIS topology. This challenging non-convex optimization problem is decomposed into two blocks based on the continuous and discrete characteristics of the optimization variables. In the first block, BS active beamforming and IRIS deployment are optimized using convex optimization and successive convex approximation algorithms, respectively. In the second block, IRIS passive beamforming and topology are addressed through a neighbor extraction cross-entropy algorithm and a proposed genetic algorithm-tabu search (GA-TS) algorithm, respectively. These two blocks are alternately optimized. Simulation results reveal three key findings: 1) compared to the traditional alternating optimization framework, the proposed BAO framework achieves rapid convergence while significantly enhancing the system’s achievable WSR; 2) optimizing the IRIS deployment is critical for mitigating the “multiplicative fading effect”, exhibiting a distinct double-peak characteristic; and 3) the proposed GA-TS algorithm closely tracks the near-optimal performance of the exhaustive search scheme, reducing computational complexity even with a limited number of RIS elements.