Sum-Rate Enhancement for RIS-Assisted Movable Antenna Systems: Joint Transmit Beamforming, Reflecting Design, and Antenna Positioning

Reconfigurable intelligent surfaces (RISs), have become a revolutionary wireless channel control paradigm as a potential solution for future 6G networks. However, in many scenarios, due to the influence of "multiple-scatterer" environments, the existing RIS-assisted multi-user systems still have limitations in terms of capacity. Therefore, this paper proposes the novel concept of active RIS-assisted movable antenna systems (MAs), which can optimize channel conditions and improve communication performance by locally moving the antenna solely in the receiving area. Additionally, the optimization problem for RIS-assisted multi-user multiple-input single-output (MU-MISO) systems, which aims to maximize the sum-rate among multiple users, also entails beamforming optimization at the base station (BS), phase shift design at the RIS, and MAs positioning. To solve this challenging and nonconvex optimization problem, in the case of a fixed MA's position, the Lagrange dual transform is used to introduce auxiliary variables to decouple the original problem into three subproblems: the optimization of auxiliary variables, the optimization of beamforming transmission on the BS, and the phase shift design of the RIS. Furthermore, to identify the optimal positions of the MAs, an adaptive fractional programming quadratic transform algorithm based on a genetic algorithm (GA) (FPQT-GA) is proposed to investigate the proposed system. The simulation results show that compared with traditional fixed antenna systems (FAs) active RIS-assisted, the employment of MAs can significantly enhance the system's overall performance in typical application scenarios.