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Spectrum Allocation in Cognitive Radio Networks by Hybrid Analytic Hierarchy Process and Graph Coloring Theory

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Machine Learning and Intelligent Communications (MLICOM 2017)

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Abstract

In this paper, a graph coloring-based spectrum allocation algorithm in cognitive radio networks combined with analytic hierarchy process is proposed. By analyzing several key factors that affect the quality of the leased spectrum, the algorithm combines the graph algorithm and analytic hierarchy process to assign the optimal spectrum to cognitive users orderly. Simulation results show that the proposed algorithm can effectively improve the network efficiency compared with original algorithms and arose inconspicuous loss to the whole network’s fairness. The proposal not only improves the efficiency of spectrum allocation, but also balances the requirements of the overall fairness of cognitive radio networks.

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Author information

Authors and Affiliations

  1. Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China

    Jianfei Shi, Feng Li, Jiangxin Zhang & Lele Cheng

  2. Dalian University of Technology, Dalian, 116024, Liaoning, China

    Xin Liu

  3. Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Mu Zhou

Authors
  1. Jianfei Shi
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  2. Feng Li
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  3. Xin Liu
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  4. Mu Zhou
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  5. Jiangxin Zhang
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  6. Lele Cheng
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Corresponding author

Correspondence to Feng Li .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Xuemai Gu

  2. Harbin Institute of Technology, Weihai, Heilongjiang, China

    Gongliang Liu

  3. Shandong University, Weihai, Heilongjiang, China

    Bo Li

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cite this paper

Shi, J., Li, F., Liu, X., Zhou, M., Zhang, J., Cheng, L. (2018). Spectrum Allocation in Cognitive Radio Networks by Hybrid Analytic Hierarchy Process and Graph Coloring Theory. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-73447-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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