低轨通信星座分域网络感知优化方法

邸航; 董涛; 刘志慧; 魏硕彤; 张启维; 张丁允

doi:10.11959/j.issn.1000-0801.2025021

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低轨通信星座分域网络感知优化方法

研究 | 更新时间：2025-07-04

- 低轨通信星座分域网络感知优化方法
- Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation
- 天地一体化信息网络 2025年6卷第2期页码：87-96
- 作者机构：
  
  1.航天恒星科技有限公司空间信息体系与融合应用全国重点实验室，北京100095
  2.北京卫星信息工程研究所，北京100095
- 作者简介：
  
  [ "邸航（1996- ），男，中国空间技术研究院博士生，主要研究方向为卫星网络资源管控、卫星网络资源感知和卫星网络资源分配等。" ]
  [ "董涛（1975- ），男，航天恒星科技有限公司研究员，主要研究方向为卫星通信、卫星网络等。" ]
  [ "刘志慧（1989- ），女，航天恒星科技有限公司研究员，主要研究方向为空间通信与网络、异构网络资源管控和网络资源感知等" ]
  [ "魏硕彤（2000- ），男，中国空间技术研究院硕士生，主要研究方向为卫星网络及控制器部署等。" ]
  [ "张启维（1995- ），男，航天恒星科技有限公司工程师，主要研究方向为卫星通信、卫星网络、MIMO空口模拟等。" ]
  [ "张丁允（2000- ），女，中国空间技术研究院硕士生，主要研究方向为卫星网络及智能路由技术等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62331027);中国科协青年人才托举工程(2022QNRC001)
- DOI：10.11959/j.issn.1000-0801.2025021
  中图分类号： V19
- 收稿日期：2025-01-20，
  
  修回日期：2025-04-30，
  
  纸质出版日期：2025-06-20
- 稿件说明：
移动端阅览
邸航,董涛,刘志慧等.低轨通信星座分域网络感知优化方法[J].天地一体化信息网络,2025,06(02):87-96.

DI Hang,DONG Tao,LIU Zhihui,et al.Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation[J].Space-Integrated-Ground Information Networks,2025,06(02):87-96.
邸航,董涛,刘志慧等.低轨通信星座分域网络感知优化方法[J].天地一体化信息网络,2025,06(02):87-96. DOI： 10.11959/j.issn.1000-0801.2025021.

DI Hang,DONG Tao,LIU Zhihui,et al.Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation[J].Space-Integrated-Ground Information Networks,2025,06(02):87-96. DOI： 10.11959/j.issn.1000-0801.2025021.

摘要

低轨通信星座网络资源异构时变、业务需求多样导致网络资源适配难，亟须高效的网络感知优化方法。针对星座负载轻的冷点区域，提出一种多源感知域动态划分及域内高效感知汇聚算法，动态求解域内最佳主动感知路径，扩大冷点区域感知范围，支撑网络感知能力提升。针对负载重的热点区域，提出基于星上队列资源感知的分步优化算法，分别通过优化节点感知频次与上报节点选择，降低感知开销与上报时间，最终支持冷热点分域网络的感知优化。

Abstract

The heterogeneous and time-varying characteristics of network resources in LEO communication constellation

as well as the diversities of service requirements

make it difficult to allocate network resources. Therefore

efficient network awareness optimization methods are urgently needed. For cold domain with lower load pressure

a multi-source dynamic awareness domain partitioning and efficient awareness aggregation algorithm is proposed. By dynamically solving the optimal active awareness path within the domain

the awareness range is expanded to support the improvement of network awareness capability. For the hot domain with higher load pressure

a stepwise optimization algorithm based on on-board queue resource awareness is proposed

which reduces awareness overhead and reporting time by respectively optimizing node awareness frequency and the selection of reporting nodes

ultimately supporting the awareness optimization of cold and hot domains in the constellation.

关键词

Keywords

references

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