Separate Channel Estimation With Hybrid RIS-Aided Multi-User Communications
Songjie Yang, Wanting Lyu, Dongli Wang, Zhongpei Zhang
Abstract
As a solution to the thorny problem of the acquisition of separate channels with the presence of the passive reconfigurable intelligent surface (RIS), the hybrid RIS architecture with several radio frequency (RF) chains is gaining popularity. In this motif, we offer a unique once-sounding estimation technique with a single RF chain-based RIS, which reduces pilot overhead in comparison to the existing twice-sounding method. In its wake, we exploit the multi-user channel characteristic to construct a measurements-augmentation-based compressive sensing (CS) framework to enhance the channel estimation performance between the base station and RIS. To boost the algorithm's practical applicability, we build a two-stage CS mechanism with the multiple measurement vector (MMV) attribute to lower the computational complexity. In addition, the hybrid RIS architecture is extended to the two-timescale estimation technique for pilot minimization. Finally, simulation results demonstrate the superiority of our proposed schemes in terms of estimation performance, pilot overhead, and computational complexity.