A Topology Design Method for Satellite Networks based on Deep Reinforcement Learning

Yuning Zheng, Yifeng Lyu, Ying Wang*, Xiufeng Sui, Liyue Zhu, Shubin Xu

*此作品的通讯作者

    科研成果: 书/报告/会议事项章节会议稿件同行评审

    摘要

    Recently, Low Earth Orbit (LEO) satellite constellations with low-latency and high-bandwidth attract extensive research. However, most available studies focused on the field of satellite network routing algorithms, ignoring the impact of topology on the efficiency of inter-satellite networking and the quality of inter-satellite communication. In this paper, we propose a satellite network topology design method based on deep reinforcement learning (DRL), with the goal of reducing the latency of the entire satellite network. To achieve this goal, we first model the satellite network communication scene and formulate the topology optimization problem as a Markov decision process (MDP). Then, we further propose the idea of backbone-point satellites and use DRL to optimize the topology structure. Finally, we conduct extensive experiments on different performances of satellite topology, and we conclude that the network topology constructed in this way can provide lower latency communications than the motif and +Grid topologies, optimized by 8.48% and 42.86% respectively.

    源语言英语
    主期刊名Eighth International Conference on Electronic Technology and Information Science, ICETIS 2023
    编辑Huajun Dong, Hu Sheng
    出版商SPIE
    ISBN(电子版)9781510666535
    DOI
    出版状态已出版 - 2023
    活动8th International Conference on Electronic Technology and Information Science, ICETIS 2023 - Dalian, 中国
    期限: 24 3月 202326 3月 2023

    出版系列

    姓名Proceedings of SPIE - The International Society for Optical Engineering
    12715
    ISSN(印刷版)0277-786X
    ISSN(电子版)1996-756X

    会议

    会议8th International Conference on Electronic Technology and Information Science, ICETIS 2023
    国家/地区中国
    Dalian
    时期24/03/2326/03/23

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    引用此

    Zheng, Y., Lyu, Y., Wang, Y., Sui, X., Zhu, L., & Xu, S. (2023). A Topology Design Method for Satellite Networks based on Deep Reinforcement Learning. 在 H. Dong, & H. Sheng (编辑), Eighth International Conference on Electronic Technology and Information Science, ICETIS 2023 文章 127151A (Proceedings of SPIE - The International Society for Optical Engineering; 卷 12715). SPIE. https://doi.org/10.1117/12.2682444