Secure Active and Passive Beamforming in IRS-Aided MIMO Systems

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Saba Asaad - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Yifei Wu - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Ali Bereyhi - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Ralf R. Muller - , Friedrich-Alexander-Universität Erlangen-Nürnberg (Autor:in)
  • Rafael F. Schaefer - , Universität Siegen (Autor:in)
  • H. Vincent Poor - , Princeton University (Autor:in)

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 is comprised of 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.

Details

OriginalspracheEnglisch
Seiten (von - bis)1300-1315
Seitenumfang16
FachzeitschriftIEEE Transactions on Information Forensics and Security
Jahrgang17
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa
Extern publiziertJa

Externe IDs

ORCID /0000-0002-1702-9075/work/165878251

Schlagworte

Schlagwörter

  • alternating optimization, fractional programming, intelligent reflecting surfaces, majorization-maximization method, Physical layer security