Energy-Efficient Multi-UAV-Assisted Integrated Sensing, Communication, and Computing for Remote Areas

Extending wireless connectivity to remote areas is essential for delivering intelligent services in critical sectors, i.e., healthcare, agriculture, and disaster management. Unmanned aerial vehicles (UAVs) have emerged as a promising solution due to their agile mobility, low deployment cost, and line-of-sight (LoS) communication capabilities. However, efficiently managing UAV resources while integrating sensing, communication, and computing (ISCC) functionalities presents significant challenges. In this paper, we propose a multi-UAV-assisted ISCC framework that simultaneously supports wireless communication links for computational task offloading, remote computing, and active target sensing. A comprehensive system model is developed, and a joint optimization problem is formulated to minimize the weighted sum energy consumption of UAVs and remote users, subject to constraints on latency, power budget, and UAV mobility. To solve the resulting non-convex problem, we design a decomposition-based solution that integrates a convex optimization technique with the deep deterministic policy gradient (DDPG) algorithm. Simulation results demonstrate the effectiveness of the proposed framework in achieving energy-efficient operation under practical system constraints.