Joint power minimization and trajectory design for collaborative communication, sensing, and computing in UAV networks

In this paper, we propose a collaborative communication, sensing, and computing (CCSC) model assisted by unmanned aerial vehicles (UAVs). Ground users (GUs) generate computing tasks and communicate with UAVs to determine whether the tasks can be processed locally or offloaded to the UAVs. While GUs have limited computing power, UAVs are equipped to handle more complex tasks and sense target states. The multi-antenna base station (BS) not only manages communication tasks with UAVs but also schedules UAV operations and assigns computational tasks. The problem of UAV trajectory design and power minimization based on communication sensing and computing is studied. Since the problem is non-convex, the original problem is solved separately by a block coordinate descent approach. To solve the power minimization problem, we propose an offloading decision algorithm based on exchange matching to solve the task offloading problem and minimize the UAV computing, hovering, and flight power. For the UAV trajectory design, we propose a UAV trajectory design algorithm based on successive convex approximation (SCA) to optimize the UAV trajectory. Simulation results show that the proposed algorithm is superior to other benchmarks such as the greedy algorithm and genetic algorithm.