基于DQN的低轨卫星网络多目标智能路由算法

罗宗屹; 金世超; 董涛; 殷杰

doi:10.11959/j.issn.2096-8930.2025003

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基于DQN的低轨卫星网络多目标智能路由算法

研究 | 更新时间：2025-04-10

- 基于DQN的低轨卫星网络多目标智能路由算法
- Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN
- 天地一体化信息网络 2025年6卷第1期页码：16-23
- 作者机构：
  
  1.航天恒星科技有限公司天地一体化信息技术国家重点实验室，北京 100095
  2.北京卫星信息工程研究所，北京 100095
- 作者简介：
  
  [ "罗宗屹（1998- ），男，硕士生，主要研究方向为卫星网络。" ]
  [ "金世超（1980- ），男，博士，航天恒星科技有限公司业务副总经理，研究员，主要研究方向为卫星通信系统与装备。" ]
  [ "董涛（1975- ），男，博士，航天恒星科技有限公司研究员，主要研究方向为卫星通信和网络。" ]
  [ "殷杰（1983- ），男，博士，航天恒星科技有限公司研究员，主要研究方向为卫星通信网络。" ]
- 基金信息：
  
  国家重点研发计划资助项目(2022YFB2902504)
- DOI：10.11959/j.issn.2096-8930.2025003
  中图分类号： TP393
- 收稿日期：2024-11-11，
  
  修回日期：2025-02-10，
  
  纸质出版日期：2025-03-20
- 稿件说明：
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罗宗屹,金世超,董涛等.基于DQN的低轨卫星网络多目标智能路由算法[J].天地一体化信息网络,2025,06(01):16-23.

LUO Zongyi,JIN Shichao,DONG Tao,et al.Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN[J].Space-Integrated-Ground Information Networks,2025,06(01):16-23.
罗宗屹,金世超,董涛等.基于DQN的低轨卫星网络多目标智能路由算法[J].天地一体化信息网络,2025,06(01):16-23. DOI： 10.11959/j.issn.2096-8930.2025003.

LUO Zongyi,JIN Shichao,DONG Tao,et al.Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN[J].Space-Integrated-Ground Information Networks,2025,06(01):16-23. DOI： 10.11959/j.issn.2096-8930.2025003.

摘要

近年来，低轨卫星网络发展迅速，被广泛应用于全球通信、互联网接入等领域。首先，对当前低轨卫星网络发展现状与主流的低轨网络路由算法进行总结。然后，针对星上路由算法设计面临的优化目标单一、收敛速度慢以及时延和丢包率等指标优化难度大等挑战，提出基于深度Q网络（DQN）的多目标智能路由算法，通过设计多目标奖励函数，实现了时延、丢包率、负载均衡多目标的性能优化。在时延方面，本算法优于最短通路优先算法；在流量分布指数和丢包率方面，本算法相较于最短通路优先算法与Dijkstra算法分别提高14 %和10 %以上。最后，阐述所提智能路由算法在多种应用场景中的使用方法。

Abstract

In recent years

LEO satellite networks have developed rapidly and are widely used in global communication and internet access. This paper first summarized the current development status of LEO networks and the main LEO network routing algorithms. At the same time

aimed at the challenges of single optimization objectives

slow convergence speed

and difficulty in optimizing indicators such as delay and packet loss

this paper proposed a multi-objective intelligent routing algorithm based on deep Q-network (DQN). With the designed DQN multi-objective reward function

it realized the optimization of delay

packet loss

load balancing. Regarding delay

the proposed algorithm is superior to the Shortest Path First (SPF) algorithm. In terms of traffic distribution index and packet loss rate

the performances of the proposed algorithm are improved by more than 14% and 10% compared with the SPF and Dijkstra algorithms respectively. In addition

this paper illustrated the application methods of the proposed intelligent routing algorithm in various scenarios.

关键词

Keywords

references

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