Abstract

Unmanned Aerial Vehicle (UAV) networks have recently gained interest, owing to the mobility of UAVs that can be exploited to improve channel conditions and user coverage. In this paper, we consider a scenario where a rotary-wing UAV is dispatched for covering a maximum number of ground users by jointly optimizing the UAV trajectory and bandwidth allocation, under constraints of pre-determined maximal total flight time and on-board energy. The problem is difficult to solve since has nonconvex constraints and includes infinite variables over time. As such, we propose an iterative algorithm with guaranteed convergence by applying block coordinate descent and successive convex approximation techniques. We further exploit the path discretization to formulate the original problem into an optimization formulation with finite variables. We deploy a UAV circular trajectory as the benchmark. The numerical results show that the proposed algorithm significantly outperforms the benchmark scheme and the bandwidth allocation can improve UAV coverage compared with the UAV trajectory only with time partitioning.

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