Improved sum-rate optimization in the multiuser MIMO downlink

We consider linear precoding and decoding in the downlink of a multiuser multiple-input, multiple-output (MIMO) system. In this scenario, the transmitter and the receivers may each be equipped with multiple antennas, and each user may receive more than one data stream. We examine the relationship between the sum capacity for the broadcast channel with channel state information at the transmitter under a sum power constraint and the achievable sum rates under linear precoding. We show that achieving the optimum sum throughput under linear precoding is equivalent to minimizing the product of mean squared error (MSE) matrix determinants. The resulting nonconvex optimization problem is solved numerically, guaranteeing local convergence only. The performance of this approach is analyzed via comparison to the sum capacity and to existing approaches for linear precoding.