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Modulation Recognition of Digital Signal Based on Decision Tree and Support Vector Machine

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Green Energy and Networking (GreeNets 2020)

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Abstract

The modulation recognition of digital signal is widely used in the field of communication. In this paper, a decision tree modulation recognition algorithm based on feature extraction and a conventional classifier recognition based on SVM are proposed. 9 kinds of common digital signals are identified and simulated. The results show that the recognition rate of SVM classifier and decision tree is high at low SNR.

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Acknowledgements

This work has been partially supported by the National Natural Science Foundation of China project (51674109) and 2017 scientific research project of basic scientific research expenses of provincial colleges and universities in Heilongjiang Province.

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Authors and Affiliations

  1. Heilongjiang University of Science and Technology, Harbin, 150022, China

    Fugang Liu, Ziwei Zhang, Shuang Zheng & Zhaoju Jia

Authors
  1. Fugang Liu
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  2. Ziwei Zhang
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  3. Shuang Zheng
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  4. Zhaoju Jia
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Corresponding author

Correspondence to Fugang Liu .

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Editors and Affiliations

  1. Heilongjiang University of Science and Technology, Harbin, China

    Xiaolin Jiang

  2. Dalian Polytehnic University, Dalian, China

    Peng Li

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Liu, F., Zhang, Z., Zheng, S., Jia, Z. (2020). Modulation Recognition of Digital Signal Based on Decision Tree and Support Vector Machine. In: Jiang, X., Li, P. (eds) Green Energy and Networking. GreeNets 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 333. Springer, Cham. https://doi.org/10.1007/978-3-030-62483-5_15

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  • DOI: https://doi.org/10.1007/978-3-030-62483-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62482-8

  • Online ISBN: 978-3-030-62483-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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