Joint Optimization of UAV Trajectory and Resource Allocation in Multi-UAV-Enabled Wireless Powered Communication Networks Under Max–Min Criterion

We consider a wireless powered communication network (WPCN) where several unmanned aerial vehicles (UAVs) serve as energy transmitters and data collectors for low-powered ground devices (GDs). During the downlink phase, UAVs wirelessly transfer energy to the GDs, allowing them to harvest power for future data transmission. In the subsequent uplink phase, the GDs use the harvested energy to send information back to their corresponding UAVs. Our goal is to optimize system performance by maximizing the minimum throughput achieved among the GDs. We reformulate the original problem as a combination of three interrelated subproblems using a block coordinate descent approach: transmit power optimization of GDs, scheduling, and UAV trajectory optimization. These subproblems are solved iteratively to achieve an optimal solution. By adaptively adjusting UAV trajectories and optimizing scheduling and power distribution, our method ensures efficient energy delivery and reliable data collection. Numerical results confirm that the proposed approach significantly outperforms conventional methods, improving minimum throughput by up to 32.7% and 59.6% compared to fixed scheduling and fixed trajectory approaches, respectively. Furthermore, the adopted Lambert W-based energy harvesting model achieves up to 41% higher harvested energy compared to existing nonlinear energy harvesting models. Our findings underscore the potential of UAV-assisted wireless power transfer in boosting the efficiency and reliability of future wireless communication networks.