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

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

TL;DR

The study tackles secure multi-user two-way communication aided by an intelligent reflecting surface (IRS) in the presence of a single eavesdropper. By formulating a max-min secrecy-rate problem over IRS phase shifts and transmit powers, and solving it via an alternating optimization framework that combines SDR/SCA for phase shifts and fractional programming for power allocation, the work delivers a convergent algorithm with strong fairness guarantees. Numerical results show substantial gains in the minimum secrecy-rate, up to 3.6x, particularly when the IRS is positioned near legitimate users, underscoring the practical potential of IRSs for physical-layer security in multi-user two-way systems. The approach provides a scalable route to improve secrecy in shared-channel networks with FD operation and multiple user-pairs.

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.

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

TL;DR

The study tackles secure multi-user two-way communication aided by an intelligent reflecting surface (IRS) in the presence of a single eavesdropper. By formulating a max-min secrecy-rate problem over IRS phase shifts and transmit powers, and solving it via an alternating optimization framework that combines SDR/SCA for phase shifts and fractional programming for power allocation, the work delivers a convergent algorithm with strong fairness guarantees. Numerical results show substantial gains in the minimum secrecy-rate, up to 3.6x, particularly when the IRS is positioned near legitimate users, underscoring the practical potential of IRSs for physical-layer security in multi-user two-way systems. The approach provides a scalable route to improve secrecy in shared-channel networks with FD operation and multiple user-pairs.

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.
Paper Structure (8 sections, 17 equations, 5 figures, 1 table, 1 algorithm)

This paper contains 8 sections, 17 equations, 5 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Minimum Secrecy-Rate Maximization
  4. IRS Phase Shift Optimization
  5. Transmit Power Optimization
  6. Alternating Optimization Algorithm
  7. Numerical Results
  8. Conclusions

Figures (5)

  • Figure 1: IRS assisted secure multi-user two-way communication model.
  • Figure 2: Positions of all nodes considered in the numerical results.
  • Figure 3: (a) Average fractional increase in minimum secrecy rate with respect to the number of sub-iterations in power optimization. (b) Variation of power optimization variables and the objective with increasing sub-iterations. Dashed lines indicate the values obtained using the alternative method.
  • Figure 4: (a) Average fractional increase in minimum secrecy rate with respect to the number of sub-iterations, when IRS phase shifts are optimized. (b) Average fractional increase in minimum secrecy rate with respect to the number of outer-iterations in Algorithm 1.
  • Figure 5: Variation of minimum secrecy rate with the number of IRS elements in four different user configurations. For configuration C1, six scenarios are created using no-IRS, IRS with random phase shifts, minimum power, maximum power, and optimized power conditions.