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9th International Conference on Communications and Networking in China

Research Article

Spectrum data mining in the cognitive radio

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/icst.chinacom.2014.256419,
        author={Feng Ren and Xuemeng Wang and Tao Peng and Chong Ma},
        title={Spectrum data mining in the cognitive radio},
        proceedings={9th International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={1},
        keywords={spectrum sensing; data mining; statistic; clustering pattern mining},
        doi={10.4108/icst.chinacom.2014.256419}
    }
    
  • Feng Ren
    Xuemeng Wang
    Tao Peng
    Chong Ma
    Year: 2015
    Spectrum data mining in the cognitive radio
    CHINACOM
    IEEE
    DOI: 10.4108/icst.chinacom.2014.256419
Feng Ren,*, Xuemeng Wang1, Tao Peng1, Chong Ma1
  • 1: Beijing University of Posts and Telecommunications
*Contact email: renfeng1010@foxmail.com

Abstract

—with the rapid development of wireless communi-cations, the ever increasing demand for limited spectrum resources will eventually cause spectrum scarcity problem. Cognitive Radio offers a solution to this problem, which intelligently detect unused spectrum and share it, without harmful interference to primary users. It has been a research hotspot on how to analyze and utilize licensed spectrum to meet the increasing need for bands. Aiming at such a problem, this paper presents a CR system model and then proposes the scheme for spectrum data mining from the large-scale of TV spectrum sensing data. According to functional requirement we designed three levels of information mining: statistical information, space clustering, and sequential pattern mining. The simulation results illustrate the effectiveness of the data mining scheme.

Keywords
spectrum sensing; data mining; statistic; clustering pattern mining
Published
2015-01-21
Publisher
IEEE
Appears in
IEEEXplore
http://dx.doi.org/10.4108/icst.chinacom.2014.256419
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