The unmanned aerial vehicle (UAV) is a promising enabler of Internet of Things (IoT) owing to its highly flexible features. Combined with wireless power transfer (WPT) techniques, a UAV can provide energy for IoT nodes, which can extend the lifetime of energy constrained communication systems. This paper studies resource and trajectory optimization in UAV-powered wireless communication systems, which consists of two UAVs and two ground nodes (GNs). The system works in a way that the two UAVs alternately charge the two GNs through wireless power transfer and two GNs also alternately send their information to the corresponding UAV with the harvested energy, which can effectively reduce the interference while receiving the information of GNs. Aiming to maximize the minimum throughput of two GNs, wireless resource and UAVs’ trajectories are jointly optimized with the constraints of UAV collision avoidance, flying speed, and transmit power. Successive convex programming (SCP) and block coordinate descent (BCD) are utilized to solve the optimization problem. Simulation results show that the proposed scheme achieves larger minimum throughput than the benchmark scheme.

由于其高度灵活的功能，无人飞行器（UAV）是物联网（IoT）的有前途的推动者。结合无线电力传输（WPT）技术，UAV可以为IoT节点提供能量，从而可以延长受能量限制的通信系统的寿命。本文研究了无人机驱动的无线通信系统中的资源和轨迹优化，该系统由两个无人机和两个地面节点（GN）组成。该系统的工作方式是两个UAV通过无线电力传输对两个GN进行交替充电，并且两个GN也将所收集的能量交替地将其信息发送到相应的UAV，这可以有效地减少接收GN信息时的干扰。为了最大化两个GN的最小吞吐量，无线资源和无人飞行器的轨迹在无人飞行器防撞，飞行速度和发射功率的约束条件下进行了联合优化。利用连续凸规划（SCP）和块坐标下降（BCD）来解决优化问题。仿真结果表明，与基准方案相比，该方案具有更高的最小吞吐率。