Secrecy Rate Optimization for Intelligent Reflecting Surface Assisted MIMO System

Zheng Chu, Wanming Hao, Pei Xiao, De Mi, Zilong Liu, Mohsen Khalily, James R. Kelly, Alexandros P. Feresidis

Research output: Journal PublicationArticlepeer-review

56 Citations (Scopus)


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.

Original languageEnglish
Article number9262884
Pages (from-to)1655-1669
Number of pages15
JournalIEEE Transactions on Information Forensics and Security
Publication statusPublished - 2021
Externally publishedYes


  • Intelligent reflecting surface
  • multiple-input multiple-output (MIMO)
  • phase shift
  • physical-layer secrecy

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


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