重庆邮电大学学报（自然科学版）2025，Vol.37Issue(4)：491-499,9.DOI:10.3979/j.issn.1673-825X.202406230153
面向地面干扰环境的无人机辅助边缘计算能效优化
Energy-efficiency optimization of UAV-assisted edge computing with ground interference
摘要
Abstract
To improve the deployment flexibility of traditional mobile edge computing(MEC)systems and enhance system performance in ground interference environments,this paper proposes a UAV-assisted edge computing scheme.Aiming to maximize the system's energy efficiency(EE)across all time slots,the UAV horizontal trajectory planning and user sched-uling within specified task times are modeled as a Markov decision process(MDP).Based on the dueling double deep Q-network(D3QN)algorithm,the communication links are optimized to enable UAVs to intelligently perceive interference,enhancing trajectory stability and thereby improving overall system energy efficiency.Simulation results demonstrate that the proposed scheme significantly outperforms benchmark methods in terms of energy efficiency improvement.关键词
无人机通信/移动边缘计算/系统能效/抗干扰/深度强化学习Key words
unmanned aerial vehicle communication/mobile edge computing/system energy efficiency/anti-jamming/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
林杰,叶蜀新,李苗,多滨,王正强,王梓斌..面向地面干扰环境的无人机辅助边缘计算能效优化[J].重庆邮电大学学报（自然科学版）,2025,37(4):491-499,9.基金项目
四川省国际科技创新合作/港澳台科技创新合作项目(2023YFH0092) （2023YFH0092）
四川省高等学校创新性实验项目"智能无人系统安全创新实验" （）
2024-2026年成都理工大学高等教育人才培养质量和教学改革项目(JG2430165,JG2420017) Sichuan International Science and Technology Innovation Cooperation/Hong Kong,Macao and Taiwan Science and Technology Innovation Cooperation Project(2023YFH0092) （JG2430165,JG2420017）
Sichuan Provincial Higher Education Institution Innovative Experiment Project"Intelligent Unmanned Systems Safety Innovation Experiment" （）
Chengdu University of Technology Higher Education Talent Training Quality and Teaching Reform Project(2024 to 2026)(JG2430165,JG2420017) （2024 to 2026）
