Weighted Sum-Rate Maximization for STAR-RIS-Aided FDD Communication Systems

Abstract

This letter investigates a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided frequency division duplexing (FDD) communication system. Since downlink (DL) and uplink (UL) signals are transmitted simultaneously in FDD, the transmission and reflection coefficients of the STAR-RIS should be optimized to support both transmissions. Considering when a single base station with multi-antenna supports multiple users, we formulate a weighted sum-rate maximization problem to consider the relative priority between the DL and UL, as well as among users. To effectively tackle the formulated non-convex optimization problem, we adopt an alternating optimization framework that decomposes it into tractable sub-problems, where the beamformers at the base station, the UL power allocation for users, and the transmission and reflection coefficients of the STAR-RIS are iteratively updated. Within this framework, a successive convex approximation-based technique is proposed to optimize the transmission and reflection coefficients of the STAR-RIS. Simulation results demonstrate that the proposed optimization framework achieves superior performance compared to benchmarks and effectively balances transmission priority.