• DocumentCode
    1491171
  • Title

    Decision-feedback equalization using multiple-hyperplane partitioning for detecting ISI-corrupted M-ary PAM signals

  • Author

    Chen, S. ; Hanzo, L. ; Mulgrew, B.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Southampton Univ., UK
  • Volume
    49
  • Issue
    5
  • fYear
    2001
  • fDate
    5/1/2001 12:00:00 AM
  • Firstpage
    760
  • Lastpage
    764
  • Abstract
    A decision-feedback equalizer scheme is derived based on multiple-hyperplane partitioning of signal space for detecting M-ary pulse amplitude modulation symbols transmitted through a noisy intersymbol interference channel. The proposed scheme is based on the fact that the optimal Bayesian decision boundary separating two neighboring signal classes is asymptotically piecewise linear and consists of several hyperplanes, when the signal-to-noise ratio tends to infinity. An algorithm is developed to determine these hyperplanes, which are then used to partition the observation signal space. The resulting detector can closely approximate the optimal Bayesian detector, at an advantage of considerably reduced detector complexity
  • Keywords
    Bayes methods; computational complexity; decision feedback equalisers; intersymbol interference; pulse amplitude modulation; signal detection; DFE; ISI-corrupted M-ary PAM signals; M-ary pulse amplitude modulation symbols; asymptotically piecewise linear; complexity reduction; decision-feedback equalization; multiple-hyperplane partitioning; noisy intersymbol interference channel; observation signal space; optimal Bayesian decision boundary; signal detection; signal-to-noise ratio tends; Amplitude modulation; Bayesian methods; Decision feedback equalizers; Detectors; Intersymbol interference; Noise level; Piecewise linear techniques; Pulse modulation; Signal detection; Signal to noise ratio;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.923797
  • Filename
    923797