基于深度学习的低轨卫星互联网建设研究  

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

作　　者：郭向梁 魏川奇 张石 GUO Xiangliang;WEI Chuanqi;ZHANG Shi(China Academy of Information and Communications Technology,Beijing 100191,China;Landspace Technology Corporation,Beijing 100176,China)

机构地区：[1]中国信息通信研究院,北京100191 [2]蓝箭航天空间科技股份有限公司,北京100176

出　　处：《数字通信世界》2024年第12期19-21,共3页Digital Communication World

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。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.

关 键 词：深度学习 卫星通信 低轨卫星 互联网建设 

分 类 号：TN927.2[电子电信—通信与信息系统] TP393.4[电子电信—信息与通信工程]