Weighted Sum-Rate Maximization by Dynamic Reconfigurable Intelligent Surface Deployment

Reconfigurable intelligent surfaces (RIS) are emerging as one of the key technologies that will drive next-generation wireless communications, primarily due to their capacity to reconfigure the wireless propagation environment. This paper investigates an RIS-assisted wireless communication system in which the RIS is mounted on a slide rail, allowing for dynamic adjustment of its location. Recognizing that the RIS channel is dependent on its location, we propose a joint optimization of the base station’s (BS) transmit beamforming, the RIS’s passive beamforming, and the RIS’s location, with the objective of maximizing the system’s weighted sum-rate (WSR). To address this joint optimization problem efficiently, we first employ a one-dimensional search method to determine the optimal RIS location. Subsequently, the problem is decomposed into two subproblems using the block coordinate descent (BCD) method, which are then solved through reduced weighted minimum mean-square error (R-WMMSE) and Riemannian manifold optimization, respectively. Extensive numerical simulations demonstrate the critical role of RIS location optimization and show that the proposed algorithm significantly enhances the system’s WSR.