Localization-assisted Communication for RIS-aided Distributed MIMO Systems Using Distributionally Robust Optimization

Reconfigurable intelligent surface (RIS)-assisted distributed multiple-input multiple-output (D-MIMO) systems rely on instantaneous channel state information (CSI) to optimize the RIS phase shifts. However, the existence of a large number of RISs and access points (APs) requires the transmission of a significant amount of pilots for CSI estimation, thus resulting in high signaling overhead. In this paper, we propose a localization-assisted communication method that utilizes location information for RIS phase shift optimization. To address the challenge introduced by localization uncertainty, we formulate a distributionally robust optimization (DRO)-based sum-rate maximization problem and then present a successive convex approximation (SCA)-based iterative algorithm to solve it. Numerical evaluations demonstrate that the proposed DRO-based beamforming method can improve the sum-rate by $31.2 \%$ compared to the robust optimization and non-robust schemes.