Weighted Sum Secrecy Rate Maximization Using Intelligent Reflecting Surface

Hehao Niu, Zheng Chu, Fuhui Zhou, Zhengyu Zhu, Miao Zhang, Kai Kit Wong

Research output: Journal PublicationArticlepeer-review

49 Citations (Scopus)


This paper aims to investigate the benefit of using intelligent reflecting surface (IRS) in multi-user multiple-input single-output (MU-MISO) systems, in the presence of eavesdroppers. We maximize the weighted sum secrecy rate by jointly designing the secure beamforming (BF), the artificial noise (AN), as well as the phase shift of the IRS. An alternating optimization (AO) method is proposed to deal with the formulated non convex problem. In particular, the secure beamforming and AN jamming matrix are optimally designed via the successive convex approximation (SCA) approach for given phase shift, which can be derived by considering the alternating direction method of multiplier (ADMM) and element-wise block coordinate decent (EBCD) methods. Finally, simulation results are presented to show the benefit of the IRS in terms of improving the secrecy performance, when compared to other methods.

Original languageEnglish
Pages (from-to)6170-6184
Number of pages15
JournalIEEE Transactions on Communications
Issue number9
Publication statusPublished - Sept 2021
Externally publishedYes


  • alternating direction method of multiplier (ADMM)
  • alternating optimization
  • element-wise block coordinate decent (EBCD)
  • Intelligent reflecting surface (IRS)
  • secure transmission

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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