移动通信2024，Vol.48Issue(9)：94-101,8.DOI:10.3969/j.issn.1006-1010.20240724-0001
基于强化学习的双簇头无人机蜂群通信抗干扰算法
Anti-Jamming Algorithm for Dual-Cluster Head UAV Swarm Communications Based on Reinforcement Learning
摘要
Abstract
Swarms of unmanned aerial vehicles(UAVs)are designed to collaborate and accomplish tasks in complex environments.However,UAV communication is highly vulnerable to electromagnetic interference,which can cause some UAVs to lose their relay forwarding capabilities.To address this issue,a reinforcement learning-based dual-cluster head anti-jamming communication algorithm for UAV swarms is proposed.The UAVs are re-clustered using the proposed dual-cluster head HEED algorithm,where two cluster heads are elected within each cluster.In inter-cluster multi-hop routing,reinforcement learning is employed to optimize the next-hop selection of the cluster head nodes.Simulation results demonstrate that,compared to the traditional HEED algorithm,the dual-cluster head HEED algorithm significantly enhances network lifetime and improves energy consumption balance.关键词
无人机/双簇头/抗干扰/强化学习Key words
unmanned aerial vehicle(UAV)/dual-cluster head/anti-jamming/reinforcement learning分类
信息技术与安全科学引用本文复制引用
杨斌善,魏琛,夏晓晨,许魁,叶子绿,耿存奕,廖程建..基于强化学习的双簇头无人机蜂群通信抗干扰算法[J].移动通信,2024,48(9):94-101,8.基金项目
国家自然科学基金"通信定位一体去蜂窝大规模MIMO智能传输方法研究","面向低空空域的无定形大规模MIMO一体化感知与通信方法研究"(62071485,62271503) （62071485,62271503）
江苏省基础研究计划"天地融合卫星移动通信组网理论与技术"(BK20192002) （BK20192002）
江苏省自然科学基金"基于无定形网络的低空空域融合感知与通信方法研究"(BK20231485) （BK20231485）
