Cost Minimization of Integrated Sensing, Communication, and Computing in UAV-Enabled Systems

Unmanned aerial vehicles (UAVs) can be deployed as powerful air relays to remedy delay-sensitive computing tasks. In this paper, we propose to adopt a fixed-position UAV equipped with over-the-air computing (AirComp) ability to support computation offloading for ground users away from the base station (BS). In light of the dual-functional communication and sensing BS antenna, we develop an integrated sensing, communication, and computing (ISCC) framework, where the BS performs the sensing task, and transmits the sensing information to the UAV, enhancing the computing schedule of the UAV. Then, three models of communication, sensing, and computing are deduced, and the total cost of the delay, accuracy, and power is minimized by jointly optimizing the task scheduling variable matrix, the proportion of communication resources, and the sensing threshold. We invoke the Lagrange multiplier method, piecewise linear approximation, and quick sorting-based task scheduling algorithm to solve the problem. Simulation results show that the proposed algorithm effectively reduces the ISCC cost compared with some existing algorithms and verifies the feasibility of the proposed algorithm.