Robust Transmission Design for Intelligent Reflecting Surface-Aided Secure Communication Systems With Imperfect Cascaded CSI

• Published in: IEEE transactions on wireless communications Vol. 20; no. 4; pp. 2487 - 2501
• Main Authors: Hong, Sheng, Pan, Cunhua, Ren, Hong, Wang, Kezhi, Chai, Kok Keong, Nallanathan, Arumugam
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antennas; Array signal processing; Beamforming; Channel estimation; Computational geometry; Convexity; Covariance matrix; Eavesdropping; imperfect CSI; Intelligent reflecting surface (IRS); Mathematical analysis; Matrix methods; Optimization; physical layer security; Probability; reconfigurable intelligent surface (RIS); Reconfigurable intelligent surfaces; robust design; Robustness; secure communications; Simulation; Statistical analysis; Transmitters; Wireless communication; Wireless communication systems; Wireless communications
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2020.3042828

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. 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.