Artificial-Noise-Aided Secure MIMO Wireless Communications via Intelligent Reflecting Surface

Hong, Sheng, Pan, Cunhua, Ren, Hong, Wang, Kezhi and Nallanathan, Arumugam (2020) Artificial-Noise-Aided Secure MIMO Wireless Communications via Intelligent Reflecting Surface. IEEE Transactions on Communications. ISSN 0090-6778 (In Press)

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Official URL: https://doi.org/10.1109/TCOMM.2020.3024621

Abstract

This paper 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.

Item Type: Article
Uncontrolled Keywords: Intelligent Reflecting Surface (IRS), Reconfigurable Intelligent Surfaces, Secure Communication, Physical Layer Security, Artificial Noise (AN), MIMO
Subjects: G900 Others in Mathematical and Computing Sciences
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 01 Dec 2020 11:26
Last Modified: 01 Dec 2020 11:30
URI: http://nrl.northumbria.ac.uk/id/eprint/44877

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