Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

TL;DR

This paper introduces a regularized channel inversion precoder optimized for maximizing secrecy sum-rate in multi-user MIMO systems with potential eavesdroppers, providing closed-form solutions and joint optimization strategies.

Contribution

It derives the optimal regularization parameter for RCI precoding under secrecy constraints and proposes a joint optimization algorithm for power and regularization, outperforming existing schemes.

Findings

RCI precoder with optimal regularization outperforms other linear schemes.

The proposed joint optimization improves secrecy sum-rate by up to 20%.

The scheme achieves the same scaling as the optimal non-secrecy RCI sum-rate.

Abstract

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter $\alpha$ and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter $\alpha_{\mathrm{LS}}$ of the precoder using large-system analysis. We show that the RCI precoder with $\alpha_{\mathrm{LS}}$ outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed $\alpha$. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing $\alpha$ and the power allocation vector. The jointly optimized precoder outperforms RCI with $\alpha_{\mathrm{LS}}$ and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.