Secure Active and Passive Beamforming in IRS-Aided MIMO Systems

Saba Asaad, Yifei Wu, Ali Bereyhi, Ralf R. Muller, Rafael F. Schaefer, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

Abstract

In intelligent reflecting surface (IRS)-aided multiple-input multiple-output (MIMO) systems, the IRS can be utilized to suppress the information leakage towards malicious terminals. This can lead to significant secrecy gains. This work exploits these gains via a tractable joint design of downlink beamformers and IRS phase-shifts. In this respect, we consider a generic IRS-aided MIMO wiretap setting and invoke fractional programming and alternating optimization to iteratively find the beamformers and phase-shifts that maximize the achievable weighted secrecy sum-rate. Our design concludes two low-complexity algorithms. Performance of the proposed algorithms are numerically evaluated and compared to the benchmark. The results reveal that integrating IRSs into MIMO systems not only boosts the secrecy performance, but also improves the robustness against passive eavesdropping.

Original languageEnglish (US)
JournalIEEE Transactions on Information Forensics and Security
DOIs
StateAccepted/In press - 2022

All Science Journal Classification (ASJC) codes

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

Keywords

  • alternating optimization
  • Array signal processing
  • Downlink
  • Eavesdropping
  • fractional programming
  • intelligent reflecting surfaces
  • majorization-maximization method
  • Massive MIMO
  • MISO communication
  • Optimization
  • Physical layer security
  • Programming

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