Transmit Designs for the MIMO Broadcast Channel with Statistical CSI
Yongpeng Wu, Shi Jin, Xiqi Gao, Matthew R. McKay, and Chengshan Xiao

TL;DR
This paper develops a low-complexity transmit design for MIMO broadcast channels with statistical CSI, optimizing the weighted sum-rate using iterative algorithms and bounds, and demonstrates its effectiveness through numerical results.
Contribution
It introduces a novel low-complexity transmission scheme based on linear assignment and bounds, improving performance in MIMO broadcast channels with statistical CSI.
Findings
The proposed scheme achieves significant performance gains.
A simplified closed-form expression for near-optimal matrices is derived.
Numerical results confirm the effectiveness of the low-complexity approach.
Abstract
We investigate the multiple-input multiple-output broadcast channel with statistical channel state information available at the transmitter. The so-called linear assignment operation is employed, and necessary conditions are derived for the optimal transmit design under general fading conditions. Based on this, we introduce an iterative algorithm to maximize the linear assignment weighted sum-rate by applying a gradient descent method. To reduce complexity, we derive an upper bound of the linear assignment achievable rate of each receiver, from which a simplified closed-form expression for a near-optimal linear assignment matrix is derived. This reveals an interesting construction analogous to that of dirty-paper coding. In light of this, a low complexity transmission scheme is provided. Numerical examples illustrate the significant performance of the proposed low complexity scheme.
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