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Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection

Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection

Faten Mashta, Mohieddin Wainakh, Wissam Altabban
Copyright: © 2020 |Volume: 11 |Issue: 4 |Pages: 19
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781799807025|DOI: 10.4018/IJERTCS.2020100103
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MLA

Mashta, Faten, et al. "Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection." IJERTCS vol.11, no.4 2020: pp.41-59. http://doi.org/10.4018/IJERTCS.2020100103

APA

Mashta, F., Wainakh, M., & Altabban, W. (2020). Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 11(4), 41-59. http://doi.org/10.4018/IJERTCS.2020100103

Chicago

Mashta, Faten, Mohieddin Wainakh, and Wissam Altabban. "Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 11, no.4: 41-59. http://doi.org/10.4018/IJERTCS.2020100103

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Abstract

Spectrum sensing in cognitive radio has difficult and complex requirements such as requiring speed and sensing accuracy at very low SNRs. In this paper, the authors propose a novel fully blind sequential multistage spectrum sensing detector to overcome the limitations of single stage detector and make use of the advantages of each detector in each stage. In first stage, energy detection is used because of its simplicity. However, its performance decreases at low SNRs. In second and third stage, the maximum eigenvalues detector is adopted with different smoothing factor in each stage. Maximum eigenvalues detection technique provide good detection performance at low SNRs, but it requires a high computational complexity. In this technique, the probability of detection improves as the smoothing factor raises at the expense of increasing the computational complexity. The simulation results illustrate that the proposed detector has better sensing accuracy than the three individual detectors and a computational complexity lies in between the three individual complexities.

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