Dynamic UAV Path Planning for 5G Mobile Base Stations: An Approach Based on the Link Budget

In the application of unmanned aerial vehicles (UAVs), dynamic path planning of communication links plays a crucial role in optimizing task execution efficiency and enhancing mobile communication quality. However, in complex environments such as post-disaster rescue, surveillance and detection, and environmental monitoring, the communication reliability of UAVs becomes particularly important. Merely optimizing the flight path is insufficient to meet communication requirements. The communication transmission speed and stability between UAVs and ground stations may significantly decrease, leading to communication interruptions, data loss, and even loss of control over the UAV. Therefore, based on link budget and in combination with dynamic path planning for UAVs, we further enhance the capability of UAVs to find optimal paths in dynamic electromagnetic field environments. We propose a dynamic path planning method for communication links in UAVs based on an improved particle swarm optimization (PSO) algorithm, and we calculate the maximum communication range allowed for dynamic base stations using 5G link budget. In this method, at each time step, we utilize the PSO algorithm to find three key points in the relatively optimal path based on the maximum communication range and the current UAV position. We fit the current optimal complete path using spline interpolation, calculate the UAV's flight trajectory from the current time step to the next, and continuously update the UAV's current position based on this trajectory. At the next time step, we recompute the current optimal path, completing the entire path planning process. Simulation results demonstrate superior performance of the proposed method, saving time costs and reducing flight path distances, thereby proving its potential in improving UAV task execution efficiency and communication reliability.