• DocumentCode
    3094766
  • Title

    Algorithm of digital modulation recognition based on support vector machines

  • Author

    Wang, Lan-Xun ; Ren, Yu-jing ; Zhang, Rui-hua

  • Author_Institution
    Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
  • Volume
    2
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    980
  • Lastpage
    983
  • Abstract
    A new algorithm based on high order cumulants (HOC) and support vector machines (SVM) for modulation and recognition of digital communication signals is proposed. The new method can identify six digital modulation signals: 2ASK, 4ASK, 8ASK, 4PSK, 8PSK and 16QAM digital signals using fourth and sixth order cumulants of the signals as vectors and SVM based on binary tree as classifiers. The method uses new class distance as rules of constructing binary tree, which separates the furthest class from others first, so that the method can maintain high generalization ability. The computer simulation results justify the method´s validity.
  • Keywords
    amplitude shift keying; digital communication; generalisation (artificial intelligence); higher order statistics; phase shift keying; quadrature amplitude modulation; signal classification; support vector machines; trees (mathematics); 16QAM digital signal; 2ASK digital signal; 4ASK digital signal; 4PSK digital signal; 8ASK digital signal; 8PSK digital signal; binary tree; digital communication signal recognition; digital modulation recognition; generalization ability; high order cumulants; signal classification; support vector machines; Binary trees; Classification tree analysis; Cybernetics; Digital modulation; Gaussian noise; Machine learning; Machine learning algorithms; Signal processing; Support vector machine classification; Support vector machines; Binary tree; High order cumulants; Modulation identification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212366
  • Filename
    5212366