Energy-Optimized Trajectory Design for UAV-Assisted WSNs with Integrated Sensing, Communication and Computation

Owing to high maneuverability, low cost, and flexible deployment capabilities, unmanned aerial vehicles (UAVs) serve as ideal aerial nodes for wireless sensor networks (WSNs) in remote areas. UAVs can function not only as communication relays between sensor nodes (SNs) and ground base stations (BSs), but also provide sensing capabilities for SN localization, and deliver computing services to the network. This paper proposes a novel UAV-assisted WSN framework integrating sensing, communication, and computation functionalities. Our objective is to minimize UAV energy consumption while enhancing the system's integrated sensing, communication, and computation (ISCC) capabilities through optimized trajectory design and task allocation strategies. The task is formulated as a non-convex optimization problem, decomposed into multiple subproblems, and solved via an iterative optimization method based on the differential evolution (DE) algorithm. Numerical results indicate that the proposed ISCC framework and optimization methodology demonstrate strong validity, achieving significant improvements in both energy conservation and enhanced ISCC performance.