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Threshold Estimation Method for Spectrum Sensing Using Bootstrap Technique

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Intelligent Computing Theories (ICIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7995))

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Abstract

In this paper, the bootstrap technique is applied to spectrum sensing for cognitive radio networks. A novel test threshold estimation method based on bootstrap is proposed. From the simulation results, it is seen that the proposed bootstrap procedure can provide satisfied detection performance while only requires the smallest samples compared with the existing methods. Therefore, the proposed method is very accurate and efficient for spectrum sensing.

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Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Guangxi University for Nationalities, Nanning, China

    Liping Luo, Wei Zhou & Huazhi Meng

Authors
  1. Liping Luo
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  2. Wei Zhou
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  3. Huazhi Meng
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. Electrical and Electronics Department, Polytechnic of Bari, Via Orabona 4, 70125, Bari, Italy

    Vitoantonio Bevilacqua

  3. Faculty of Engineering, District University Francisco José de Caldas, Cra. 7a No. 40-53, Fifth Floor, Bogotá, Colombia

    Juan Carlos Figueroa

  4. School of Electrical, Computer and Telecommunications Engineering, The University of Wollongong, 2522, North Wollongong, NSW, Australia

    Prashan Premaratne

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Luo, L., Zhou, W., Meng, H. (2013). Threshold Estimation Method for Spectrum Sensing Using Bootstrap Technique. In: Huang, DS., Bevilacqua, V., Figueroa, J.C., Premaratne, P. (eds) Intelligent Computing Theories. ICIC 2013. Lecture Notes in Computer Science, vol 7995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39479-9_43

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  • DOI: https://doi.org/10.1007/978-3-642-39479-9_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39478-2

  • Online ISBN: 978-3-642-39479-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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