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Spectrum Sensing Methods for Cognitive Radio Networks: A Review

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Abstract

The main spectrum sensing (SS) techniques suitable for cognitive radio networks (CRNs) such as energy, matched filter, covariance and Hadamard ratio-based detectors are analyzed. Principal methods and concepts associated with SS-CRNs are explored while numerical simulation experiments and comparison analysis are interpreted aiming to corroborate those concepts and demonstrate the effectiveness and drawbacks of those well-established SS-CRN techniques and methods.

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Notes

  1. In terms of linear dependence of the number of samples (log scale) increasing with the SNR (in dB) decreasing.

  2. For a better detailed description of the noise model and uncertainty models used in this work, please refer to [35].

  3. The channel scenario case studied herein for the CAV detector.

  4. Actually MfS needs an entire pilot sequence.

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Acknowledgements

This work was supported in part by the National Council for Scientific and Technological Development (CNPq) of Brazil under Grant 304066/2015-0, Fundação Araucária under Grant 302/2012, and in part by State University of Londrina—Paraná State Government (UEL), and CAPES/DS scholarship.

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  1. Electrical Engineering Department, State University of Londrina (DEEL-UEL), Rod. Celso Garcia Cid - PR445, s/n, Campus Universitário, Po. Box 10.011, Londrina, PR, 86057-970, Brazil

    Lucas Claudino & Taufik Abrão

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Claudino, L., Abrão, T. Spectrum Sensing Methods for Cognitive Radio Networks: A Review. Wireless Pers Commun 95, 5003–5037 (2017). https://doi.org/10.1007/s11277-017-4143-1

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