Large System Achievable Rate Analysis of RIS-Assisted MIMO Wireless Communication With Statistical CSIT

Reconfigurable intelligent surface (RIS) is an emerging technology to enhance wireless communication in terms of energy cost and system performance by equipping a considerable quantity nearly passive reflecting elements. This study focuses on downlink RIS-assisted multiple-input multiple-output (MIMO) that comprises three links Rician channel, including base station (BS) RIS, RIS user, BS user. The objective design optimal transmit covariance matrix at diagonal phase-shifting maximize the achievable ergodic rate exploiting statistical channel state information BS. Therefore, large-system approximation derived using replica method large dimension random theory. enables identification asymptotic-optimal matrices alternating optimization algorithm. Simulation results show are consistent with calculated Monte-Carlo averaging. verify proposed algorithm can significantly MIMO performance.