Semi-Blind Channel Estimation for RIS-Aided Massive MIMO: A Trilinear AMP Approach

This paper studies semi-blind channel estimation for a reconfigurable intelligent surface (RIS) aided uplink massive multiple-input multiple-output (MIMO) system, in which the base station simultaneously estimates the channel coefficients and detects the partially unknown transmit symbols. We formulate the semi-blind channel estimation task as a trilinear inference problem. Based on the approximate message passing (AMP) principle, we develop a computationally efficient approach, called Trilinear AMP, to calculate the marginal posterior mean estimators of the trilinear inference problem. Simulation results demonstrate the effectiveness of the proposed Trilinear AMP approach.