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

Hong, Sheng, Pan, Cunhua, Ren, Hong, Wang, Kezhi, Chai, Kok Keong and Nallanathan, Arumugam (2021) Robust Transmission Design for Intelligent Reflecting Surface-Aided Secure Communication Systems With Imperfect Cascaded CSI. IEEE Transactions on Wireless Communications, 20 (4). pp. 2487-2501. ISSN 1536-1276

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Official URL: https://doi.org/10.1109/twc.2020.3042828

Abstract

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.

Item Type: Article
Uncontrolled Keywords: Intelligent reflecting surface (IRS), reconfigurable intelligent surface (RIS), robust design, imperfect CSI, physical layer security, secure communications
Subjects: G400 Computer Science
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 18 Jun 2021 14:59
Last Modified: 18 Jun 2021 15:06
URI: http://nrl.northumbria.ac.uk/id/eprint/46489

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