Outage analysis and optimization for IRS-UAV-assisted FSO systems under malicious jamming

This paper proposes a robust design for a free-space optical (FSO) system assisted by an unmanned aerial vehicle (UAV) equipped with an intelligent reflecting surface (IRS), operating under probabilistic malicious jamming. The UAV-carried IRS establishes an auxiliary link when the direct path is blocked. The system experiences composite fading (saturated turbulence, pointing errors, and angle-of-arrival fluctuations), and the jammer's intermittent activity is modeled by a Bernoulli process. We derive a closed-form expression for the average outage probability (OP) under this unified channel-and-jamming model. To address the critical performance-cost trade-off, a bi-objective optimization problem is formulated to jointly minimize the OP and the hardware deployment cost. An alternating optimization (AO) algorithm is proposed to solve the resulting mixed-integer nonlinear programming problem by decoupling it into discrete (number of IRS elements) and continuous (power, angles, apertures) subproblems, which are efficiently handled via integer search and particle swarm optimization, respectively. Simulation results demonstrate that the proposed AO algorithm converges within 15 iterations, substantially faster than genetic algorithm and random search, and achieves a near-optimal trade-off, reducing outage probability by an order of magnitude compared to non-optimized benchmarks while keeping hardware cost within budget.