TRICE: An Efficient Channel Estimation Framework for RIS-Aided MIMO Communications

Reconfigurable intelligent surfaces (RISs) have been proposed recently as an enabling technology for tuning the wireless propagation channel between transceivers. To realize RISs advantages, however, accurate channel state information is required. In this paper, we consider a single-user RIS-aided system model and propose a two-stage high-resolution channel parameter estimation framework termed TRICE that exploits the low-rank nature of millimeter-wave MIMO channels. In both stages, we formulate the channel parameter estimation problem as a 2D direction-of-arrival estimation problem, for which several solution methods exist in the literature. Based on this formulation, we resort to a 2D DFT beamspace ESPRIT method to estimate the angular parameters of the involved communication channels. Our numerical results show that the proposed TRICE framework has a lower training overhead, as compared to benchmark methods, which makes it appealing in practical applications.