STAR-RIS Aided Fluid Antenna System: A Joint Optimization With Discrete Positions and Phases

In this paper, we investigate a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided fluid antenna downlink communication system, where the antennas’ locations are limited to discrete positions. Specifically, the beamforming and the positions of fluid antennas at the base station (BS), the transmission and reflection coefficients of the STAR-RIS are jointly optimized to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of the users, while satisfying the transmit power constraint at the BS and the discrete phase constraint at the STAR-RIS. To address the non-convex optimization problem, an alternating optimization (AO) algorithm is proposed. Within this framework, the non-convex SINR constraints for the BS beamforming subproblem are tackled using the successive convex approximation (SCA), while the STAR-RIS coefficients are optimized via a penalty-based method. Furthermore, to handle the discrete antenna position variables, an iterative approach based on the McCormick envelope technique is developed to find the optimal locations. Numerical results are provided to confirm the effectiveness of our proposed algorithm.