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

2025-01-24

AI Summary

This paper addresses physical-layer security enhancement in intelligent reflecting surface (IRS)-assisted multi-user two-way secure communication systems, aiming to maximize the minimum secrecy rate among all user pairs to improve robustness against eavesdropping attacks. Method: For the first time, the max-min fairness criterion is introduced into the IRS-aided two-way secure communication framework. A joint optimization of base station transmit power and IRS passive phase shifts is proposed. The non-convex power allocation problem is tackled via fractional programming, while the IRS phase optimization is solved using semidefinite relaxation; an efficient alternating iterative algorithm is designed. Results: Simulation results demonstrate that when the IRS is deployed proximal to legitimate users, the proposed scheme achieves a minimum secrecy rate 3.6× higher than baseline schemes, significantly strengthening the security robustness of the system’s weakest link.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Search and Optimization: Non-convex Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

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.

Problem

• Intelligent Reflecting Surface
• Secure Bidirectional Communication
• Enhanced Communication Security

Innovation

• Intelligent Reflecting Surface (IRS)
• Secure Communication
• Power Allocation and IRS Phase Adjustment