Max-Min Fairness for IRS-Assisted Secure Two-Way Communications
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.
Cite
@article{arxiv.2501.14270,
title = {Max-Min Fairness for IRS-Assisted Secure Two-Way Communications},
author = {Harindu Jayarathne and Tharindu Wickremasinghe and Kasun T. Hemachandra and Tharaka Samarasinghe and Saman Atapattu},
journal= {arXiv preprint arXiv:2501.14270},
year = {2025}
}
Comments
This paper has been accepted for presentation at IEEE Wireless Communications and Networking Conference (WCNC) 2025