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An Analysis of Periodogram Based on a Discrete Cosine Transform for Spectrum Sensing

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Abstract

One of the complex problems nowadays in communication systems is the lack of frequency spectrum. To solve this problem, cognitive radio is considered the best candidate that can opportunistically exploit the spectrum. The periodogram based spectrum sensing technique can be used to detect the spectrum in cognitive radio. It is a useful technique since does not need to prior information about the primary signal. In this paper, a new periodogram is presented using the Discrete Cosine Transform (DCT). Results are analyzed and compared with the current raw periodogram. It is observed that the DCT periodogram outperforms the raw technique in terms of probabilities of false alarm and detection, variance, and complexity. In addition, the lowest power of DCT coefficients can be removed without compromising the sensing performance. The proposed system shows high probability of detection with low probability of false alarm even in the case of low Signal-to-Noise Ratio (SNR).

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Authors and Affiliations

  1. Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    Emad H. Salman, Nor K. Noordin, Shaiful J. Hashim & Fazirulhisyam Hashim

  2. Department of Communications Engineering, College of Engineering, University of Diyala, Baquba, Diyala, Iraq

    Emad H. Salman

  3. Department of Computer and Communication Systems Engineering and Wireless and Photonics Network (WiPNet) Research Center, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    Nor K. Noordin

  4. Malaysian Reaserch Institute of Aging, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    Chee K. Ng

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  1. Emad H. Salman
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  2. Nor K. Noordin
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  3. Shaiful J. Hashim
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Correspondence to Emad H. Salman.

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Salman, E.H., Noordin, N.K., Hashim, S.J. et al. An Analysis of Periodogram Based on a Discrete Cosine Transform for Spectrum Sensing. Wireless Pers Commun 101, 1261–1279 (2018). https://doi.org/10.1007/s11277-018-5761-y

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  • DOI: https://doi.org/10.1007/s11277-018-5761-y

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