In this correspondence, we compare the achievable throughput for the optimal strategy of dirty paper coding (DPC) to that achieved with suboptimal and lower complexity linear precoding techniques (zero-forcing and block diagonalization). Both strategies utilize all available spatial dimensions and therefore have the same multiplexing gain, but an absolute difference in terms of throughput does exist. The sum rate difference between the two strategies is analytically computed at asymptotically high SNR. Furthermore, the difference is not affected by asymmetric channel behavior when each user has a different average SNR. Weighted sum rate maximization is also considered. In the process, it is shown that allocating user powers in direct proportion to user weights asymptotically maximizes weighted sum rate.

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broad-cast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interfence-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20 % gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100 % gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.

We study the MIMO broadcast channel and compare the achievable throughput for the optimal strategy of dirty paper coding to that achieved with sub-optimal and lower complexity linear precoding (e.g., zero-forcing and block diagonalization) transmission. Both strategies utilize all available spatial dimensions and therefore have the same multiplexing gain, but an absolute difference in terms of throughput does exist. The sum rate difference between the two strategies is analytically computed at asymptotically high SNR, and it is seen that this asymptotic statistic provides an accurate characterization at even moderate SNR levels. Weighted sum rate maximization is also considered, and a similar quantification of the throughput difference between the two strategies is computed. In the process, it is shown that allocating user powers in direct proportion to user weights asymptotically maximizes weighted sum rate.

We study the MIMO broadcast channel and compare the achievable throughput for the optimal strategy of dirty paper coding to that achieved with sub-optimal and lower complexity linear precoding (e.g., zero-forcing and block diagonalization) transmission. Both strategies utilize all available spatial dimensions and therefore have the same multiplexing gain, but an absolute difference in terms of throughput does exist. The sum rate difference between the two strategies is analytically computed at asymptotically high SNR, and it is seen that this asymptotic statistic provides an accurate characterization at even moderate SNR levels. Furthermore, the difference is not affected by asymmetric channel behavior when each user a has different average SNR. Weighted sum rate maximization is also considered, and a similar quantification of the throughput difference between the two strategies is performed. In the process, it is shown that allocating user powers in direct proportion to user weights asymptotically maximizes weighted sum rate. For multiple antenna users, uniform power allocation across the receive antennas is applied after distributing power proportional to the user weight. Index Terms Multiple antenna or MIMO, broadcast channel, high SNR analysis, zero-forcing, block diagonalization,

Linear transmission methods and feedback for downlink MIMO systems