• DocumentCode
    3250387
  • Title

    A novel modulation recognition technique based on artificial bee colony algorithm in the presence of multipath fading channels

  • Author

    Ozen, Asli ; Ozturk, Cengizhan

  • Author_Institution
    Nuh Naci Yazgan Univ., Kayseri, Turkey
  • fYear
    2013
  • fDate
    2-4 July 2013
  • Firstpage
    239
  • Lastpage
    243
  • Abstract
    In this paper, a novel automatic modulation recognition (AMR) method has been proposed for classifying of the transmitted signals by observing the received data samples in the presence of additive white Gaussian noise (AWGN) and multipath fading channel. The proposed method (ABC-ANN) is based on artificial neural network (ANN) which is trained by artificial bee colony (ABC) algorithm. Because high order statistics are very interesting features to solve the problem of AMR, the high order cumulants have been employed in the proposed ABC-ANN classifier. ABC algorithm is used in finding the optimal weight set of artificial neural networks for classification and the performance of the proposed ABC-ANN algorithm is compared with the performance of ANN classifier (SCG-ANN) using scaled conjugate gradient learning algorithm. Computer simulation results have demonstrated that the proposed recognizer can reach much better classification accuracy than the SCG-ANN in even 0 dB of signal to noise ratio (SNR) value.
  • Keywords
    AWGN; conjugate gradient methods; fading channels; learning (artificial intelligence); modulation; neural nets; optimisation; signal classification; telecommunication computing; ABC-ANN method; ANN classifier; AWGN; additive white Gaussian noise; artificial bee colony algorithm; artificial neural network; automatic modulation recognition method; conjugate gradient learning algorithm; modulation recognition technique; multipath fading channel; optimal weight set; transmitted signal classification; Artificial neural networks; Binary phase shift keying; Classification algorithms; Feature extraction; Signal to noise ratio; Training; Automatic modulation recognition; artificial bee colony algorithm; artificial neural networks; high order cumulant;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications and Signal Processing (TSP), 2013 36th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4799-0402-0
  • Type

    conf

  • DOI
    10.1109/TSP.2013.6613928
  • Filename
    6613928