부산대학교 도서관

Reconfigurable intelligent surface (RIS) is intended as a potential technique for future 6-th Generation wireless communication system. However, acquiring accurate channel state information is challenging since the channel matrices are high-dimensional due to large number of reflective elements (REs) in RIS. In this paper, we investigate the problem of sparse channel estimation (CE) in massive multiple-input multiple-output (MIMO) system equipped with large RIS (IRIS), where there are only few REs that are active during CE phase. We propose a two-stage tensor based CE algorithm that exploits the merits of IRIS. Specifically, IRIS act as reflector in the first stage of CE. Then, we identify the condition for the IRIS to activate few specified REs in the second stage. Simulation results demonstrate that the proposed algorithm outperforms existing CE schemes.