Joint Resource Allocation and 3-D Deployment for Multi-UAV Covert Communications

Unmanned aerial vehicles (UAVs)-assisted wireless communication will play an important role in the next-generation mobile communication network. However, the inherent open nature of the signal propagation environment may cause illegal eavesdropping and surveillance from adversaries. In addition, the intergroup co-channel interference among different cells further degrades the system performance. Hence, we consider a generic scenario of multiple UAV base stations (UAV-BSs) and ground users, where multiple terrestrial wardens attempt to detect the transmissions from UAV-BSs to users and a UAV-mounted jammer is employed to generate artificial noise to assist the covert communications. To ensure fairness, we formulate an optimization problem to maximize the minimum of the average rate lower bounds of all users by jointly optimizing user association, bandwidth allocation, UAV transmit power control, and UAV 3-D deployment, subject to the constraints of the detection error probability of each warden. To solve this mixed-integer nonconvex problem, we propose a suboptimal algorithm by applying block coordinate descent (BCD) method to solve three subproblems iteratively. Specifically, in each iteration, the subproblem of user association and bandwidth allocation is solved by a customized genetic algorithm (GA) first, where a closed-form expression for bandwidth allocation is obtained. Second, the subproblem of UAV transmit power control is solved by using successive convex approximation (SCA) techniques. Finally, suboptimal 3-D positions of the UAVs are obtained through particle swarm optimization (PSO)-based algorithm. Extensive simulation results demonstrate the effectiveness and superiority of our proposed algorithm compared to benchmark schemes in terms of improving the minimum of the average rate lower bounds of all users.