• DocumentCode
    817668
  • Title

    Survey of automatic modulation classification techniques: classical approaches and new trends

  • Author

    Dobre, O.A. ; Abdi, A. ; Bar-Ness, Y. ; Su, W.

  • Author_Institution
    Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland
  • Volume
    1
  • Issue
    2
  • fYear
    2007
  • fDate
    4/1/2007 12:00:00 AM
  • Firstpage
    137
  • Lastpage
    156
  • Abstract
    The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power, carrier frequency and phase offsets, timing information and so on, blind identification of the modulation is a difficult task. This becomes even more challenging in real-world scenarios with multipath fading, frequency-selective and time-varying channels. With this in mind, the authors provide a comprehensive survey of different modulation recognition techniques in a systematic way. A unified notation is used to bring in together, under the same umbrella, the vast amount of results and classifiers, developed for different modulations. The two general classes of automatic modulation identification algorithms are discussed in detail, which rely on the likelihood function and features of the received signal, respectively. The contributions of numerous articles are summarised in compact forms. This helps the reader to see the main characteristics of each technique. However, in many cases, the results reported in the literature have been obtained under different conditions. So, we have also simulated some major techniques under the same conditions, which allows a fair comparison among different methodologies. Furthermore, new problems that have appeared as a result of emerging wireless technologies are outlined. Finally, open problems and possible directions for future research are briefly discussed.
  • Keywords
    demodulation; modulation; signal classification; automatic recognition; demodulation; intelligent receiver; likelihood function; modulation classification techniques; signal detection;
  • fLanguage
    English
  • Journal_Title
    Communications, IET
  • Publisher
    iet
  • ISSN
    1751-8628
  • Type

    jour

  • DOI
    10.1049/iet-com:20050176
  • Filename
    4167652