Separate Channel Estimation and Data Detection for Semi-Passive RIS-Empowered Massive MIMO

Youzhi Xiong, Shifei Ding, Sanshan Sun, Li Liu, Zhongpei Zhang, Songjie Yang, Ning Wei

Abstract: This letter investigates the channel estimation and data detection for semi-passive reconfigurable intelligent surface (RIS) assisted millimeter wave massive multiple-input-multiple-output systems. We first achieve the coarse user-to-RIS and RIS-to-base station channels by leveraging partial active elements at the RIS. We then develop a double-layer bilinear generalized approximate message passing (DL-BiGAMP) algorithm to refine the individual channels and recover data symbols. The numerical results demonstrate that the proposed DL-BiGAMP technique can improve the performance of the channel estimation and data detection compared with other counterparts.