Research on CSI feedback of RIS-assisted massive MIMO system based on manifold learning

To solve the problem of high feedback overhead in a multi-user massive multiple-input multiple-output (MIMO) system assisted by a reconfigurable intelligent surface (RIS) in frequency-division duplexing (FDD) mode, a channel state information (CSI) feedback framework based on manifold learning was proposed. Firstly, the framework achieved initial feedback overhead reduction by simplifying the CSI feedback process. Then, the framework combined the manifold learning to train two set of dictionaries to achieve dimension reduction and reconstruction of incremental CSI. Finally, the original channel was restored at the base station. The simulation results show that the CSI feedback scheme proposed in this paper has lower overhead and complexity than the existing methods in the multi-user and limited scattering environment, and the reconstruction quality is significantly improved.