PARAFAC Decomposition based Channel Estimation for RIS-aided Multi-User MISO Wireless Communications

Reconfigurable Intelligent Surface (RIS) has recently appeared as a potential candidate technology for future wireless communications with the principal goal of realizing a Smart Radio Environment (SRE), which considers the propagation environment as a controllable element. To reinforce the advantages of the RIS, Channel State Information (CSI) to and from the RIS has to be required. In this paper, we consider a multi-user MISO uplink communication system based on RIS and implement two channel estimation algorithms based on the PARAllel FACtor decomposition (PARAFAC), which are Least Squares (LS) and Alternating Least Squares (ALS), in two different scenarios, transmitarray and reflectarray. Simulation results show that the performance of the proposed channel estimation algorithms based on PARAFAC decomposition is improved with random channel matrices initializations.