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Recognition of OFDM and SCLD Signals Based on Second-Order Statistics

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Advances in Ubiquitous Networking 2 (UNet 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 397))

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Abstract

This work addresses the problem of the modulation recognition signal in the context of cognitive radio. In particular, the discrimination between OFDM (Orthogonal Frequency Division Multiplexing) and SCLD (Single Carrier Linear Digitally) signals. We present a new method based on second order statistics. The main advantages of this method are fast, robust in a context of AWGN (Additive White Gaussian Noise) channel, frequency and timing offsets. Computer simulations are provided in order to illustrate the behavior of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Faculté des Sciences Dhar EL Mehraz, LIMS, USMBA, Fes, Morocco

    Mohamed Firdaoussi & Mohamed El-Kamili

  2. Faculté des Sciences Et Technique, LSSC, USMBA, Fes, Morocco

    Hicham Ghennioui

Authors
  1. Mohamed Firdaoussi
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  2. Hicham Ghennioui
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  3. Mohamed El-Kamili
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Corresponding author

Correspondence to Mohamed Firdaoussi .

Editor information

Editors and Affiliations

  1. Computer Science Laboratory (LIA), University of Avignon, Avignon, France

    Rachid El-Azouzi

  2. Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Daniel Sadoc Menasche

  3. Hassan II University of Casablanca, ENSEM, Casablanca, Morocco

    Essaïd Sabir

  4. CREATE-NET, Trento, Italy

    Francesco De Pellegrini

  5. INPT, Rabat, Morocco

    Mustapha Benjillali

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Firdaoussi, M., Ghennioui, H., El-Kamili, M. (2017). Recognition of OFDM and SCLD Signals Based on Second-Order Statistics. In: El-Azouzi, R., Menasche, D.S., Sabir, E., De Pellegrini, F., Benjillali, M. (eds) Advances in Ubiquitous Networking 2. UNet 2016. Lecture Notes in Electrical Engineering, vol 397. Springer, Singapore. https://doi.org/10.1007/978-981-10-1627-1_25

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  • DOI: https://doi.org/10.1007/978-981-10-1627-1_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1626-4

  • Online ISBN: 978-981-10-1627-1

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