Trade-off between Radar Sensing and Energy Consumption in Integrated Sensing, Computing, and Communication UAV Network

In this paper, a multi-UAV enabled integrated sensing, computing, and communication (ISCAC) model is proposed, in which multi-UAV senses ground Users and offloads sensing data to a high altitude platform (HAP) for processing through mobile edge computing (MEC) technology. To maximize sensing data acquisition while minimizing energy consumption, we formulate our optimization problem as a trade-off between UAV radar sensing and energy consumption. We transform the established non-convex problem into three subproblems: sensing scheduling optimization, UAV transmit power optimization, and UAV-HAP trajectory optimization. We solved these subproblems using successive convex approximation (SCA) and relaxation methods, and proposed a three-layer iterative optimization algorithm to solve the original optimization problem. Simulation results demonstrate that, compared to the benchmark scheme, the algorithm proposed in this paper can significantly improve system performance.