Triple-Structured Sparsity-Based Channel Feedback for RIS-Assisted MU-MIMO System

Reconfigurable intelligent surface (RIS) has attracted tremendous research attention in recent years. However, for RIS-assisted multi-user multiple-input multiple-output (MU-MIMO) system, downlink channel feedback in frequency division duplex (FDD) mode is quite a huge challenge due to the enlarged cascaded channel dimension. Consequently, feedback overhead turns unaffordable for RIS-assisted FDD model but limited studies focus on this puzzle. In this letter, we exploit the specific triple-structured sparsity of beamspace cascaded channel and propose a novel overhead-reduced feedback scheme. The common parameters shared by all users, i.e., path angles at BS side, offset values and amplitude ratios are transmitted back via partial active users, while the remaining user-specific information is compressed and quantized for efficient feedback. Simulation results show that under the same sum-rate requirement, the feedback overhead is further reduced by 56.8% compared with the previous studies.