Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace

Research Article

Research of Frequency Allocation Based on Improved Genetic Algorithm

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  • @INPROCEEDINGS{10.4108/eai.27-8-2020.2294697,
        author={Bo Li and Yunyi Zhai and Fugang Sun and Kun He and Richeng Guo and Cuican Wang},
        title={Research of Frequency Allocation Based on Improved Genetic Algorithm},
        proceedings={Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2020},
        month={11},
        keywords={spectrum allocation genetic algorithm sequential allocation interference model convergence speed},
        doi={10.4108/eai.27-8-2020.2294697}
    }
    
  • Bo Li
    Yunyi Zhai
    Fugang Sun
    Kun He
    Richeng Guo
    Cuican Wang
    Year: 2020
    Research of Frequency Allocation Based on Improved Genetic Algorithm
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.27-8-2020.2294697
Bo Li1, Yunyi Zhai2, Fugang Sun1, Kun He1, Richeng Guo1, Cuican Wang1,*
  • 1: Systems Engineering Research Institute
  • 2: Beijing University of Posts and Telecommunications
*Contact email: libo1669@163.com

Abstract

With the development of science and technology, more and more attention has been paid to wireless spectrum allocation technology. In this paper, we propose a improved genetic algorithm which is suitable for spectrum allocation on open space platforms. It uses the method of sequential allocation and solves the problem of channel multiplexing by a new designed interference model under the situation of tight spectrum resources. The simulation results show that the improved genetic algorithm can effectively reduce the total interference of signal and improve the convergence speed of realloction after the number of devices has changed.