Joint Precoding Design and Location Optimization in Joint Communication, Sensing and Computing of UAV Systems

In this paper, we propose a joint communication, sensing and computing (JCSC) framework for unmanned aerial vehicle (UAV) system that utilizes mobile edge computing (MEC) technology to offload radar sensing data to the ground for processing. To achieve optimal performance in sensing data processing, it is necessary to design the communication and radar precoding matrix of the UAV systems and optimize the location of the UAV system. The joint optimization model is established using the linear weighting method, which transforms the joint optimization problem into a single objective optimization problem. To solve this problem, the master problem is decomposed into two subproblems: one for precoding design in data offloading and the other for precoding design in radar sensing. Fractional programming and successive convex approximation (SCA) are used to transform each of these subproblems respectively into a convex problem, and two algorithms named "precoding design and location optimization for data offloading (PLDO)" and "precoding design and location optimization for radar sensing (PLRS)" are proposed to solve the optimization problem. The simulation results show that the proposed algorithm can greatly reduce the energy consumption of UAV compared to local processing, and it has a faster convergence speed.