Work

Energy-Efficient 3D Trajectory Optimization and Resource Allocation for UAV-Enabled ISAC Systems

Year: 2026

Type: article

Abstract: Owing to their high flexibility, autonomous operation, and rapid deployment capability, unmanned aerial vehicles (UAVs) serve as effective aerial platforms for sensing and communication in remote and time-critical scenarios. However, their limited onboard energy budget poses a significant bottleneck for sustained operations. This paper investigates an energy-efficient UAV-assisted integrated sensing and communication (ISAC) system, aiming to maximize the sensing energy efficiency (SEE), defined as the ratio of the total radar estimation rate to the total energy consumption. Unlike prior works focused solely on rate maximization or fairness, our design jointly optimizes the UAV's 3D trajectory, task scheduling, and power allocation under kinematic and coverage constraints to maximize the SEE. To solve the formulated non-convex fractional programming problem, we propose an efficient iterative algorithm based on the Dinkelbach method and block coordinate descent (BCD). Simulation results demonstrate that the proposed scheme achieves a superior trade-off between sensing performance and energy consumption.

Source: Entropy

DOI: 10.3390/e28020248

Authors: Lulu Jing, Hai Wang, Zhen Qin, Yicheng Zhao, Yi Zhu, Wensheng Zhao

Institutions: Nanjing Forestry University, PLA Army Engineering University, PLA Academy of Military Science, PAP Non-commissioned Officer School

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137