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Wireless channel extraction analyzing based on graph theory

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Abstract

Wireless channels comprise various signal characteristics that correspond to different features. This research applies digital signal processing to first excavate and categorize various features found in the channel data. Then, borrowing from graph theory, fast clustering analysis and decision tree modeling are introduced to identify unique “fingerprint” characteristics. Finally, two scenarios were tested using artificial neural networks to identify and verify their applicability in different geographical locations.

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Authors and Affiliations

  1. College of Information Science and Technology, Hainan University, Haikou, 570228, P.R. China

    Biyuan Yao, Jianhua Yin & Hui Li

  2. Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, 572000, P.R. China

    Wei Wu

Authors
  1. Biyuan Yao
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  2. Jianhua Yin
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  3. Hui Li
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  4. Wei Wu
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Correspondence to Biyuan Yao.

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Yao, B., Yin, J., Li, H. et al. Wireless channel extraction analyzing based on graph theory. Aut. Control Comp. Sci. 50, 233–243 (2016). https://doi.org/10.3103/S014641161604009X

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  • DOI: https://doi.org/10.3103/S014641161604009X

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