PSO Based Sum Rate Optimization for MU-MIMO Linear Precoder with Imperfect CSI

It is well known that if the perfect CSI is available at the BS, achieving the maximum sum throughput is equivalent to minimizing the product of mean square error matrix determinants (PDetMSE). Due to the presence of background noise in the estimated signal, the channel estimation errors are unavoidable. Hence, in this paper, it is assumed that the imperfect CSI is available at the BS and the channel estimation error variance is known at the transmitter. It is shown that maximizing the achievable sum rate is not exactly equal to minimizing the PDetMSE if the channel estimation error variance is included in the system design. Particle Swarm Optimization algorithm is used here to solve the sum rate maximization problem under the imperfect CSI. The simulation results compare the proposed system, which considers the channel estimation error variance as an integral part of the system design, with an existing system which assumes the perfect CSI at the transmitter side.