In this paper, we investigate the downlink multiple-input-multipleoutput(MIMO) broadcast channels in which a base transceiver station (BTS) broadcastsmultiple data streams to K MIMO mobile stations (MSs) simultaneously. In orderto maximize the weighted sum-rate (WSR) of the system subject to thetransmitted power constraint, the design problem is to find the pre-codingmatrices at BTS and the decoding matrices at MSs. However, such a designproblem is typically a nonlinear and nonconvex optimization and, thus, it isquite hard to obtain the analytical solutions. To tackle with the mathematicaldifficulties, we propose an efficient stochastic optimization algorithm tooptimize the transceiver matrices. Specifically, we utilize the linear minimummean square error (MMSE) Wiener filters at MSs. Then, we introduce theconstrained particle swarm optimization (PSO) algorithm to jointly optimize theprecoding and decoding matrices. Numerical experiments are exhibited tovalidate the effectiveness of the proposed algorithm in terms of convergence,computational complexity and total WSR.
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