Jamming Mitigation for Mixed RF/FSO Relay Networks Under Simultaneous Interceptions

Jamming Mitigation for Mixed RF/FSO Relay Networks Under Simultaneous Interceptions

V. H. Le, T. T. Nguyen, K. K. Nguyen, V. A. Mba and S. Singh, “Jamming Mitigation for Mixed RF/FSO Relay Networks Under Simultaneous Interceptions,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 6819-6824, doi: 10.1109/GLOBECOM54140.2023.10436735.

Abstract or Summary

In this paper, we design a jamming mitigation plan to protect a mixed radio frequency/free-space optical (RF/FSO) relay network in the context that both RF and FSO systems are simultaneously attacked by enemy jammers. Our design aims to jointly optimize the power allocation (PA) and Field-of-View (FoV) tuning strategy to maximize the RF uplink sum rate subject to practical constraints on the jamming mitigation in both FSO and RF systems. In order to address the underlying non-convex optimization problem, we first derive the closed-form expression of the optimal Fo V angle. Then, the optimal FoV angle solution is used to solve the optimization PA. Since the PA problem has a non-convex form, we use an advanced technique of first-order Taylor approximation with difference of convex functions (D.C) method to solve it. Moreover, based on the Multi-Agent Deep Reinforcement Learning (MADRL) method, we develop a MADRL-based jamming mitigation algorithm to obtain the optimized solution of PA in near real-time. The numerical results show that the performance of the proposed MADRL-based jamming mitigation algorithm with low computational complexity is close to that of the optimization method.

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