无线电通信技术2025，Vol.51Issue(5)：929-939,11.DOI:10.3969/j.issn.1003-3114.2025.05.006
面向通信空白场景的DRL辅助FANET双跳信息增强路由协议
DRL-assisted FANET Double-Hop Information Enhanced Routing Protocol for Communication Blackout Scenarios
摘要
Abstract
To address the challenge of high end-to-end delay in Flying Ad Hoc Network(FANET)under communication blackout scenarios,this paper proposes a Deep Reinforcement Learning(DRL)-assisted Double-Hop Information Enhanced Routing Protocol(DHRP).The proposed protocol models the routing process as a Markov Decision Process(MDP)to enable effective decision-making.In constructing the state space,it incorporates both node location information and link channel capacity,while considering network in-formation within a two-hop neighborhood.Centered on a deep value network,the protocol employs a reward function that reflects real-time network dynamics to guide the agent in selecting the optimal next-hop node.Simulation results show that,compared to existing ap-proaches,DHRP significantly reduces the average end-to-end delay in FANET under communication blackout conditions.Furthermore,DHRP demonstrates strong adaptability and robustness across various node densities and levels of network congestion by leveraging real-time environmental awareness and an intelligent decision-making mechanism to maintain overall network performance.关键词
飞行自组网/通信空白/深度强化学习/双跳信息/路由协议Key words
FANET/communication blackout/DRL/double-hop information/routing protocol分类
信息技术与安全科学引用本文复制引用
郭歆莹,李明,朱春华..面向通信空白场景的DRL辅助FANET双跳信息增强路由协议[J].无线电通信技术,2025,51(5):929-939,11.基金项目
国家自然科学基金(61901159) （61901159）
河南工业大学青年骨干教师培养计划(21420104)National Natural Science Foundation of China(61901159) （21420104）
Cultivation Programme for Young Backbone Teachers in Henan University of Technology(21420104) （21420104）
