• DocumentCode
    1855045
  • Title

    A simple and robust modulation classification method via counting

  • Author

    Huo, Xiaoming ; Donoho, David

  • Author_Institution
    Dept. of Stat., Stanford Univ., CA, USA
  • Volume
    6
  • fYear
    1998
  • fDate
    12-15 May 1998
  • Firstpage
    3289
  • Abstract
    Automatic modulation classification (or recognition) is an intrinsically interesting problem with a variety of regulatory and military applications. We developed a method which is simple, fast, efficient and robust. The feature being used is the counts of signals falling into different parts of the signal plane. Compared with the likelihood method and the high order correlation method, it is much easier to be implemented, and the execution is much faster. When the channel model is correct, our method is efficient, in the sense that it will achieve the “optimal” classification rate. When unknown contamination is present, our method can automatically overcome it to certain degree. At SNRs of 10 and 15 dB, examples of classifying two modulation types-QAM4 and PSK6-are given. Simulations demonstrate its ability to deal with unknown noise
  • Keywords
    pattern classification; phase shift keying; quadrature amplitude modulation; 10 dB; 15 dB; PSK6; QAM4; SNR; automatic modulation classification; automatic modulation recognition; channel model; counting; efficient method; high order correlation method; likelihood method; military application; modulation classification method; noise; optimal classification rate; regulatory applications; robust method; signal plane; simulations; Additive noise; Contamination; Correlation; Gaussian noise; Geometry; Magnetohydrodynamics; Noise robustness; Partitioning algorithms; Signal to noise ratio; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-4428-6
  • Type

    conf

  • DOI
    10.1109/ICASSP.1998.679567
  • Filename
    679567