Joint Resource Allocation and Trajectory Design for UAV-Assisted Covert Coverage Maximization

The successful and complete downlink transmission of critical data from an unmanned aerial vehicle (UAV) base station, such as control command and intelligence information, is essential for ground users to perform specific tasks in adversarial scenarios. In this paper, we propose to employ a UAV to disseminate data to ground users aiming at meeting their data demand, where a warden attempts to detect the transmission. To maximize the covert coverage, we formulate an optimization problem to maximize the number of served users through joint resource allocation and UAV trajectory design. To solve the formulated mixed-integer non-convex problem, we first relax the original problem and then propose a penalty-based two-loop iterative algorithm. Specifically, the resource allocation and the UAV trajectory are alternatively optimized by employing the block successive convex approximation (BSCA) method in the inner loop, while the Lagrangian penalty multipliers are updated in the outer loop. Simulation results have validated the fast convergence and performance superiority of our proposed method compared to the benchmarks in the literature.