For LEO satellite networks: Intelligent interference sensing and signal reconstruction based on blind separation technology

Chengjie Li, Lidong Zhu, Zhen Zhang
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Abstract

In LEO satellite communication networks, the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker, and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.
用于低地轨道卫星网络:基于盲区分离技术的智能干扰感应和信号重建
在低地球轨道卫星通信网络中,卫星数量急剧增加,卫星的相对速度非常快,电子信号混叠现象时有发生。这些混叠信号使得信号接收机的接收能力变差,信号处理能力变弱,通信系统的抗干扰能力降低。针对上述问题,为了节省通信资源,提高通信效率,同时考虑到干扰信号的不规则性,欠定盲分离技术可以有效地解决这种情况下的干扰感知和信号重构问题。为了提高源信号分离的稳定性和信息传输的安全性,可以执行贪婪优化算法。同时,为了提高网络信息传输效率,防止算法陷入局部最优,可在每次迭代过程中删除低能点。最终,仿真实验验证了本文提出的算法既提高了网络传输系统的传输效率,又提高了通信系统的安全性,实现了低地轨道卫星通信系统中干扰感应和信号重构的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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