This article considers an artificial noise (AN)-aided secure MIMO wireless communication system. To enhance the system security performance, the advanced intelligent reflecting surface (IRS) is invoked, and the base station (BS), legitimate information receiver (IR) and eavesdropper (Eve) are equipped with multiple antennas. With the aim for maximizing the secrecy rate (SR), the transmit precoding (TPC) matrix at the BS, covariance matrix of AN and phase shifts at the IRS are jointly optimized subject to constrains of transmit power limit and unit modulus of IRS phase shifts. Then, the secrecy rate maximization (SRM) problem is formulated, which is a non-convex problem with multiple coupled variables. To tackle it, we propose to utilize the block coordinate descent (BCD) algorithm to alternately update the variables while keeping SR non-decreasing. Specifically, the optimal TPC matrix and AN covariance matrix are derived by Lagrangian multiplier method, and the optimal phase shifts are obtained by Majorization-Minimization (MM) algorithm. Since all variables can be calculated in closed form, the proposed algorithm is very efficient. We also extend the SRM problem to the more general multiple-IRs scenario and propose a BCD algorithm to solve it. Simulation results validate the effectiveness of system security enhancement via an IRS.

中文翻译：

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通过智能反射面的人工噪声辅助安全 MIMO 无线通信

本文考虑了人工噪声 (AN) 辅助的安全 MIMO 无线通信系统。为增强系统安全性能，调用先进的智能反射面（IRS），为基站（BS）、合法信息接收器（IR）和窃听器（Eve）配备多根天线。为了最大化保密率 (SR)，在发射功率限制和 IRS 相移单位模数的约束下，联合优化了 BS 的发射预编码 (TPC) 矩阵、AN 的协方差矩阵和 IRS 的相移. 然后，制定了保密率最大化（SRM）问题，这是一个具有多个耦合变量的非凸问题。为了解决这个问题，我们建议利用块坐标下降 (BCD) 算法来交替更新变量，同时保持 SR 不减少。具体而言，最优TPC矩阵和AN协方差矩阵通过拉格朗日乘子法得到，最优相移通过Majorization-Minimization(MM)算法得到。由于所有变量都可以以封闭形式计算，因此所提出的算法非常有效。我们还将 SRM 问题扩展到更一般的多 IR 场景，并提出了 BCD 算法来解决它。仿真结果验证了通过 IRS 增强系统安全性的有效性。我们还将 SRM 问题扩展到更一般的多 IR 场景，并提出了 BCD 算法来解决它。仿真结果验证了通过 IRS 增强系统安全性的有效性。我们还将 SRM 问题扩展到更一般的多 IR 场景，并提出了 BCD 算法来解决它。仿真结果验证了通过 IRS 增强系统安全性的有效性。