Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks

作     者：Yixin HUANG Shufan WU Zeyu KANG Zhongcheng MU Hai HUANG Xiaofeng WU Andrew Jack TANG Xuebin CHENG Yixin HUANG;Shufan WU;Zeyu KANG;Zhongcheng MU;Hai HUANG;Xiaofeng WU;Andrew Jack TANG;Xuebin CHENG

作者机构：School of Aeronautics and AstronauticsShanghai Jiao Tong UniversityShanghai 200240China School of AstronauticsBeihang UniversityBeijing 100191China School of AerospaceMechanical and Mechatronic EngineeringThe University of SydneyCamperdown 2006Australia X-LaboratoryThe Second Academy of China Aerospace Science and Industry CorporationBeijing 100854China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2023年第36卷第2期

页      面：284-291页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：co-supported by the National Natural Science Foundation of China(No.U20B2056) the office of Military and Civilian Integration Devel-opment Committee of Shanghai(No.2020-jmrh1-kj25) the X LAB Joint Innovation Foundation with the Second Academy of CASIC(No.21GFC-JJ02-322) 

主　　题：LEO satellite networks Mega constellation Multi-objective optimization Routing algorithm Reinforcement learning 

摘      要：Recently,mega Low Earth Orbit(LEO)Satellite Network(LSN)systems have gained more and more attention due to low latency,broadband communications and global coverage for ground *** of the primary challenges for LSN systems with inter-satellite links is the routing strategy calculation and maintenance,due to LSN constellation scale and dynamic network topology *** order to seek an efficient routing strategy,a Q-learning-based dynamic distributed Routing scheme for LSNs(QRLSN)is proposed in this *** achieve low end-toend delay and low network traffic overhead load in LSNs,QRLSN adopts a multi-objective optimization method to find the optimal next hop for forwarding data *** results demonstrate that the proposed scheme can effectively discover the initial routing strategy and provide long-term Quality of Service(QoS)optimization during the routing maintenance *** addition,comparison results demonstrate that QRLSN is superior to the virtual-topology-based shortest path routing algorithm.