Robust Precoding Designs for Multiuser MIMO Systems with Limited Feedback

TL;DR

This paper introduces robust precoding methods for multiuser MIMO systems with limited feedback, effectively compensating for quantization errors to enhance achievable rates.

Contribution

It proposes new robust precoding designs based on second-order channel statistics, including non-iterative MMSE and iterative WMMSE algorithms, improving performance over traditional methods.

Findings

Significant rate improvements with proposed precoding schemes.

Effective compensation for quantization errors.

Enhanced robustness in limited feedback scenarios.

Abstract

It has been well known that the achievable rate of multiuser multiple-input multiple-output systems with limited feedback is severely degraded by quantization errors when the number of feedback bits is not sufficient. To overcome such a rate degradation, we propose new robust precoding designs which can compensate for the quantization errors. In this paper, we first analyze the achievable rate of traditional precoding designs for limited feedback systems. Then, we obtain an approximation of the second-order statistics of quantized channel state information. With the aid of the derived approximation, we propose robust precoding designs in terms of the mean square error (MSE) with conditional expectation in non-iterative and iterative fashions. For the non-iterative precoding design, we study a robust minimum MSE (MMSE) precoding algorithm by extending a new channel decomposition. Also, in the case of iterative precoding, we investigate a robust weighted MMSE (WMMSE) precoding to further improve the achievable rate. Simulation results show that the proposed precoding schemes yield significant improvements over traditional precoding designs.