• DocumentCode
    607701
  • Title

    A new modulation recognition method based on Artificial Bee Colony algorithm

  • Author

    Ozen, Asli ; Ozturk, Cengizhan

  • Author_Institution
    Elektrik ve Elektron. Muhendisligi Bolumu, Nuh Naci Yazgan Univ., Kayseri, Turkey
  • fYear
    2013
  • fDate
    24-26 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new digital modulation recognition method has been proposed for classifying baseband signals that are subjected to additive white Gaussian noise (AWGN) channel in this paper. The proposed method (ABC-ANN) is based on artificial neural network (ANN) which is trained by artificial bee colony (ABC) algorithm. The high order cumulants have been employed in the proposed ABC-ANN classifier. ABC algorithm has been used in finding the optimal weight set which directly affects the performance of artificial neural networks. Computer simulation results have demonstrated that the proposed recognizer can reach much better classification accuracy than the existing methods in even -5 dB of signal to noise ratio (SNR) value.
  • Keywords
    AWGN channels; neural nets; optimisation; signal classification; ANN; AWGN channel; additive white Gaussian noise channel; artificial bee colony algorithm; artificial neural network; baseband signal classification; digital modulation recognition method; Artificial neural networks; Binary phase shift keying; Classification algorithms; Digital modulation; Signal to noise ratio; ABC algorithm; ABC-ANN; Modulation recognition; high order cumulant; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2013 21st
  • Conference_Location
    Haspolat
  • Print_ISBN
    978-1-4673-5562-9
  • Electronic_ISBN
    978-1-4673-5561-2
  • Type

    conf

  • DOI
    10.1109/SIU.2013.6531362
  • Filename
    6531362