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For leo satellite networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

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China communications 2024年第2期21卷 85-95页

作者： Chengjie Li Lidong Zhu Zhen Zhang The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and Technology(Southwest Minzu University)Chengdu 610000China National Key Laboratory of Science and Technology on communications(University of Electronic Science and Technology of China) Chengdu 610000China College of Computer Science(Sichuan University) Chengdu 610000China

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.

关键词： blind source separation greedy optimization algorithm interference sensing leo satellite communication networks signal reconstruction

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