Joint Resource Allocation and Trajectory Optimization for Completion Time Minimization for Energy-Constrained UAV Communications

An unmanned-aerial-vehicle (UAV)-aided communication scenario is studied in this research, where a UAV with constrained on-board battery capacity communicates with multiple ground users (GUs) during the flying process. We investigate the UAV trajectory as well as the resource allocation to minimize the time consumption of the specific task. The formulated problem is non-convex with innumerable variables. To make this problem tractable, a collection of line segments are utilized to represent the real trajectory through discretization. The reformulated problem is solved by applying the block coordinate descent (BCD) algorithm. To be specific, the reformulated problem is decoupled into two subproblems, i.e., resource allocation and trajectory optimization subproblems. The subproblems are both non-convex, which are efficiently resolved with the successive convex approximation (SCA) method. Then the result is obtained with an iterative algorithm. The simulation results reveal that, in comparison to benchmark schemes, the system performance has a significant improvement.

Automated summary

This research focuses on a UAV-aided communication scenario where a UAV with constrained onboard battery capacity communicates with multiple ground users during its flight. The trajectory and resource allocation of the UAV are investigated to minimize the time consumption for a specific task. To tackle the non-convex problem with numerous variables, a collection of line segments is used to discretize the real trajectory. The reformulated problem is then solved through the block coordinate descent algorithm by decoupling it into resource allocation and trajectory optimization subproblems, which are efficiently resolved using the successive convex approximation method. Simulation results demonstrate significant improvement in system performance compared to benchmark schemes.