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Dual-Feature Spectrum Sensing Exploiting Eigenvalue and Eigenvector of the Sampled Covariance Matrix

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 516))

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Abstract

The signal can be charactered by both eigenvalues and eigenvectors of covariance matrix. However, the existing detection methods only exploit the eigenvalue or eigenvector. In this paper, we utilize both eigenvalues and eigenvectors of the sampled covariance matrix to perform spectrum sensing for improving the detection performance. The features of eigenvalues and eigenvectors are considered integratedly, and the relationship between the false-alarm probability and the decision threshold is offered. To testify this method, some simulations are carried out. The results demonstrate that the method shows some advantages in the detection performance over the conventional method only adapting eigenvalues or eigenvectors.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (NSFC) (Grant No. 61671176).

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Authors and Affiliations

  1. Harbin University of Commerce, Harbin, 150028, Heilongjiang, China

    Yanping Chen

  2. Harbin Institute of Technology, Harbin, 150080, Heilongjiang, China

    Yulong Gao

Authors
  1. Yanping Chen
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  2. Yulong Gao
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Corresponding author

Correspondence to Yulong Gao .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Chen, Y., Gao, Y. (2020). Dual-Feature Spectrum Sensing Exploiting Eigenvalue and Eigenvector of the Sampled Covariance Matrix. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_103

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_103

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6503-4

  • Online ISBN: 978-981-13-6504-1

  • eBook Packages: EngineeringEngineering (R0)

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