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Secrecy Rate Optimization for Intelligent Reflecting Surface Assisted MIMO System

Chu, Zheng and Hao, Wanming and Xiao, Pei and Mi, De and Liu, Zilong and Khalily, Mohsen and Kelly, James R and Feresidis, Alexandros P (2020) 'Secrecy Rate Optimization for Intelligent Reflecting Surface Assisted MIMO System.' IEEE Transactions on Information Forensics and Security, 16. pp. 1655-1669. ISSN 1556-6013

Secrecy Rate Optimization - AAM.pdf - Accepted Version

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This paper investigates the impact of intelligent reflecting surface (IRS) enabled wireless secure transmission. Specifically, an IRS is deployed to assist multiple-input multiple-output (MIMO) secure system to enhance the secrecy performance, and artificial noise (AN) is employed to introduce interference to degrade the reception of the eavesdropper. To improve the secrecy performance, we aim to maximize the achievable secrecy rate, subject to the transmit power constraint, by jointly designing the precoding of the secure transmission, the AN jamming, and the reflecting phase shift of the IRS. We first propose an alternative optimization algorithm (i.e., block coordinate descent (BCD) algorithm) to tackle the non-convexity of the formulated problem. This is made by deriving the transmit precoding and AN matrices via the Lagrange dual method and the phase shifts by the Majorization-Minimization (MM) algorithm. Our analysis reveals that the proposed BCD algorithm converges in a monotonically non-decreasing manner which leads to guaranteed optimal solution. Finally, we provide numerical results to validate the secrecy performance enhancement of the proposed scheme in comparison to the benchmark schemes.

Item Type: Article
Uncontrolled Keywords: Intelligent reflecting surface; physical-layer secrecy; multiple-input multiple-output (MIMO); phase shift
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 21 Sep 2021 10:33
Last Modified: 23 Sep 2022 19:44

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