系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (1): 237-243.doi: 10.3969/j.issn.1001-506X.2021.01.29

• 通信与网络 • 上一篇    下一篇

基于LSTM的LEO卫星链路自适应算法

胡晓月1,2(), 康凯2,3(), 钱骅2(), 张舜卿1()   

  1. 1. 上海大学通信与信息工程学院, 上海 200444
    2. 中国科学院上海高等研究院, 上海 201210
    3. 中国科学院上海微系统与信息技术研究所无线传感网与通信重点实验室, 上海 200050
  • 收稿日期:2020-04-11 出版日期:2020-12-25 发布日期:2020-12-30
  • 作者简介:胡晓月(1995-),女,博士研究生,主要研究方向为卫星通信。E-mail:huxiaoyue1109@163.com|康凯(1977-)男,高级工程师,博士,主要研究方向为无线通信物理层。E-mail:kangk@sari.ac.cn|钱骅(1976-),男,研究员,博士,主要研究方向为无线通信物理层与信号处理。E-mail:qianh@sari.ac.cn|张舜卿(1982-),男,教授,博士,主要研究方向为5G/5G+移动通信系统、下一代WiFi网络、异构计算技术。E-mail:shunqing@shu.edu.cn
  • 基金资助:
    国家自然科学基金(61671436)

Link adaptation algorithm based on LSTM network for LEO satellite

Xiaoyue HU1,2(), Kai KANG2,3(), Hua QIAN2(), Shunqing ZHANG1()   

  1. 1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
    2. Shanghai Institute of Advanced Studies, Chinese Academy of Sciences, Shanghai 201210, China
    3. Key Laboratory of Wireless Sensor Networks and Communications, Shanghai Institute of Microsystem and
  • Received:2020-04-11 Online:2020-12-25 Published:2020-12-30

摘要:

低地球轨道(low earth orbit, LEO)卫星由于其传输损耗低、地面干扰小等优点成为空天地一体化网络的重要组成部分。由于星地传输链路的时延大,现有卫星通信过程无法实时地进行信息交互,导致系统无法适应信道的变化。针对这个问题,提出了基于长短期记忆(long short-term memory, LSTM)网络的信噪比(signal to noise ratio, SNR)预测方法,并利用预测的SNR调整系统的调制与编码方案(modulation and coding scheme, MCS),使其与快速变化的信道相匹配。仿真结果表明,提出的基于LSTM网络的SNR预测方法可以达到较高的准确度,并且根据预测的SNR实时调整MCS的方案大幅度地提高了系统的总吞吐量。

关键词: 低轨道卫星通信, 系统吞吐量, 信噪比预测, 长短期记忆网络, 调制与编码方案

Abstract:

Low earth orbit (LEO) satellite becomes an important part of the space-air-ground integrated network for its low transmission loss and little terrestrial interference. Due to the large delay of satellite-to-ground transmission link, the existing satellite communication process cannot achieve real-time channel state information interaction, which leads to the system's inability to adapt to the change of channel status. To solve this problem, an signal to noise ratio (SNR) prediction method based on long short-term memory (LSTM) network is proposed. Modulation and coding scheme (MCS) can be adjusted based on the predicted SNR to match the rapidly changing channel. Simulation results show that the proposed SNR prediction method based on LSTM network can achieve high accuracy, and the adjustment of MCS based on the predicted SNR in real-time can greatly improve the overall throughput of the system.

Key words: low orbit satellite communication, system throughput, signal to noise ratio (SNR) prediction, long short-term memory (LSTM) network, modulation and coding scheme

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