基于深度学习的低轨卫星互联网建设研究

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摘要：为提升卫星通信的效率和质量，该文聚焦低轨卫星互联网，运用深度学习理论，创新性地提出一种低轨卫星网络算法。通过明确系统运行问题，构建多智能体算法系统，以优化低轨卫星互联网建设，满足高质量通信需求，为卫星通信行业发展提供新思路与经验借鉴。

关键词：深度学习；卫星通信；低轨卫星；互联网建设

doi：10.3969/J.ISSN.1672-7274.2024.12.007

中图分类号：TN 927+.2；TP 393.4          文献标志码：A            文章编码：1672-7274（2024）12-00-03

Application Research on Low-Orbit Satellite Internet Construction Based on Deep Learning

GUO Xiangliang WEI Chuanqi ZHANG Shi

（1. China Academy of Information and Communications Technology， Beijing 100191， China;

2. Landspace Technology Corporation， Beijing 100176， China）

Abstract： To enhance the efficiency and quality of satellite communications， this paper focuses on low-orbit satellite internet and innovatively proposes a low-orbit satellite network algorithm using deep learning theory. By identifying system operational issues and constructing a multi-agent algorithm system， we aim to optimize the construction of low-orbit satellite internet to meet high-quality communication demands， providing new insights and experiences for the development of the satellite communication industry.

Keywords： deep learning; satellite communication; low-orbit satellite; Internet construction

0   引言

随着物联网技术的蓬勃发展，卫星通信网络中的用户终端节点数量急剧增加，这一趋势正有力推动着卫星通信行业的快速进步。（剩余4182字）