In this paper, we investigate the design of robust and secure transmission in intelligent reflecting surface (IRS) aided wireless communication systems. In particular, a multi-antenna access point (AP) communicates with a single-antenna legitimate receiver in the presence of multiple single-antenna eavesdroppers, where the artificial noise (AN) is transmitted to enhance the security performance. Besides, we assume that the cascaded AP-IRS-user channels are imperfect due to the channel estimation error. To minimize the transmit power, the beamforming vector at the transmitter, the AN covariance matrix, and the IRS phase shifts are jointly optimized subject to the outage rate probability constraints under the statistical cascaded channel state information (CSI) error model that usually models the channel estimation error. To handle the resulting non-convex optimization problem, we first approximate the outage rate probability constraints by using the Bernstein-type inequality. Then, we develop a suboptimal algorithm based on alternating optimization, the penalty-based and semidefinite relaxation methods. Simulation results reveal that the proposed scheme significantly reduces the transmit power compared to other benchmark schemes.
翻译:在本文中,我们调查了智能反射表面辅助无线通信系统的强势和安全传输设计。特别是,在多个单线反射发射器的监听器在场的情况下,一个多线访问点(AP)与一个单线合法接收器进行通信,其中人造噪音(AN)被传输以加强安全性能。此外,我们假设,由于频道估计错误,分级的AP-IRS用户频道不完善。为了最大限度地减少传输力、发射机的波束成形矢量、AN变量矩阵和IRS阶段转移,在统计级联频道状态信息模式下,通常模拟频道估计错误的超值概率限制下,共同优化了该级访问点。要处理由此产生的非康氏优化问题,我们首先通过使用伯恩斯坦型的不平等来估计超值概率限制。然后,我们开发了一种基于交替优化、基于惩罚和半定型放松方法的亚差算法。模拟结果显示,拟议的计划大大降低了与其他基准计划相比的传输力。