• DocumentCode
    1359980
  • Title

    Decision feedback equaliser design using support vector machines

  • Author

    Chen, S. ; Gunn, S. ; Harris, C.J.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Southampton Univ., UK
  • Volume
    147
  • Issue
    3
  • fYear
    2000
  • fDate
    6/1/2000 12:00:00 AM
  • Firstpage
    213
  • Lastpage
    219
  • Abstract
    The conventional decision feedback equaliser (DFE) that employs a linear combination of channel observations and past decisions is considered. The design of this class of DFE is to construct a hyperplane that separates the different signal classes. It is well known that the popular minimum mean square error (MMSE) design is generally not the optimal minimum bit error rate (MBER) solution. A strategy is proposed for designing the DFE based on support vector machines (SVMs). The SVM design achieves asymptotically the MBER solution and is superior in performance to the usual MMSE solution. Unlike the exact MBER solution, this SVM solution can be computed very efficiently
  • Keywords
    adaptive equalisers; decision feedback equalisers; error statistics; learning systems; least mean squares methods; MBER solution; MMSE design; MMSE solution; adaptive equaliser; channel observations; decision feedback equaliser design; hyperplane; learning approach; linear-combiner DFE; minimum mean square error; optimal minimum bit error rate; past decisions; signal classes separation; support vector machines;
  • fLanguage
    English
  • Journal_Title
    Vision, Image and Signal Processing, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-245X
  • Type

    jour

  • DOI
    10.1049/ip-vis:20000360
  • Filename
    852302