通信学报2026，Vol.47Issue(2)：83-93,11.DOI:10.11959/j.issn.1000-436x.2026003
基于GAT的分布式联合路由与频谱接入机制
GAT-based decision mechanism for decentralized joint routing and spectrum access
摘要
Abstract
To address the limited situational awareness and high decision coupling of traditional routing and spectrum ac-cess methods in dynamic network topologies,a joint optimization framework that integrates graph attention networks(GAT)with deep reinforcement learning(DRL)was proposed.The distributed path establishment process was formu-lated as a partially observable Markov decision process(POMDP),enabling hop-by-hop decentralized decisions via DRL.GAT was implemented to aggregate local observations to capture irregular topologies and inter-node interference,improving adaptability to complex environments.During training,prioritized experience replay enhances sample effi-ciency.Extensive simulations under random,clustered,and multi-flow scenarios demonstrate the method's effective-ness:in random topologies,it achieves approximately 10%higher bottleneck throughput while reducing both channel switching frequency and path hop count.In clustered topologies,it reduces channel switches by about 10%and hop count by about 13%,and in multi-flow scenarios,its performance is comparable to baseline approaches.关键词
图注意力网络/深度强化学习/路由/频谱接入Key words
graph attention network/deep reinforcement learning/routing/spectrum access分类
信息技术与安全科学引用本文复制引用
周子铂,任保全,钟旭东,刘琦,秦蓁..基于GAT的分布式联合路由与频谱接入机制[J].通信学报,2026,47(2):83-93,11.基金项目
中国博士后科学基金资助项目(No.2025M784510) China Postdoctoral Science Foundation(No.2025M784510) （No.2025M784510）
