At present, unmanned aerial vehicles (UAVs) have been widely used in communication systems, and the fifth-generation wireless system (5G) has further promoted the vigorous development of them. The trajectory planning of UAV is an important factor that affects the timeliness and completion of missions, especially in scenarios such as emergency communications and post-disaster rescue. In this paper, we consider an emergency communication network where a UAV aims to achieve complete coverage of potential underlaying device-to-device (D2D) users. Trajectory planning issues are grouped into clustering and supplementary phases for optimization. Aiming at trajectory length and sum throughput, two trajectory planning algorithms based on K-means are proposed, respectively. In addition, in order to balance sum throughput with trajectory length, we present a joint evaluation index. Then relying on this index, a third trajectory optimization algorithm is further proposed. Simulation results show the validity of the proposed algorithms which have advantages over the well-known benchmark scheme in terms of trajectory length and sum throughput.

当前，无人飞行器（UAV）已被广泛地用于通信系统中，并且第五代无线系统（5G）进一步促进了它们的蓬勃发展。无人机的轨迹规划是影响任务的及时性和完成度的重要因素，尤其是在紧急通信和灾后救援等场景中。在本文中，我们考虑了一种应急通信网络，其中，UAV旨在完全覆盖潜在的底层设备到设备（D2D）用户。轨迹规划问题分为聚类阶段和补充阶段，以进行优化。针对轨迹长度和总吞吐量，分别提出了两种基于K-means的轨迹规划算法。另外，为了平衡总吞吐量和轨迹长度，我们提出了一个联合评估指标。然后根据该指标，进一步提出了第三种轨迹优化算法。仿真结果表明了所提算法的有效性，在轨迹长度和总吞吐率方面均优于著名的基准方案。