Max-Min Fairness for IRS-Assisted Secure Two-Way Communications

This paper investigates an intelligent reflective surface (IRS) assisted secure multi-user two-way communication system. The aim of this paper is to enhance the physical layer security by optimizing the minimum secrecy-rate among all user-pairs in the presence of a malicious user. The optimization problem is converted into an alternating optimization problem consisting of two sub-problems. Transmit power optimization is handled using a fractional programming method, whereas IRS phase shift optimization is handled with semi-definite programming. The convergence of the proposed algorithm is investigated numerically. The performance gain in minimum secrecy-rate is quantified for four different user configurations in comparison to the baseline scheme. Results indicate a 3.6-fold gain in minimum secrecy rate over the baseline scheme when the IRS is positioned near a legitimate user, even when the malicious user is located close to the same legitimate user.

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Publication Details

Published
2025-03-24
DOI
https://doi.org/10.1109/wcnc61545.2025.10978502
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
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Max-Min Fairness for IRS-Assisted Secure Two-Way Communications

Kasun T. Hemachandra, Tharaka Samarasinghe, Harindu Jayarathne, Saman Atapattu et al.
Cryptography and Data Security
article

Max-Min Fairness for IRS-Assisted Secure Two-Way Communications

Kasun T. Hemachandra, Tharaka Samarasinghe, Harindu Jayarathne, Saman Atapattu, Tharindu Wickremasinghe
article en

Abstract

This paper investigates an intelligent reflective surface (IRS) assisted secure multi-user two-way communication system. The aim of this paper is to enhance the physical layer security by optimizing the minimum secrecy-rate among all user-pairs in the presence of a malicious user. The optimization problem is converted into an alternating optimization problem consisting of two sub-problems. Transmit power optimization is handled using a fractional programming method, whereas IRS phase shift optimization is handled with semi-definite programming. The convergence of the proposed algorithm is investigated numerically. The performance gain in minimum secrecy-rate is quantified for four different user configurations in comparison to the baseline scheme. Results indicate a 3.6-fold gain in minimum secrecy rate over the baseline scheme when the IRS is positioned near a legitimate user, even when the malicious user is located close to the same legitimate user.

University of Moratuwa (LK), RMIT University (AU)
Openalex Percentile: Top 96%
Cryptography and Data Security
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Max-Min Fairness for IRS-Assisted Secure Two-Way Communications — Kasun T. Hemachandra, Tharaka Samarasinghe, et al. · (2025) | TGRS Research Map | TGRS