• DocumentCode
    1749122
  • Title

    UMTS channel equalization using neural networks: natural gradient algorithm

  • Author

    Abdulkader, H. ; Langlet, F. ; Roviras, D. ; Castanie, F.

  • Author_Institution
    ENSEEIHT, Toulouse, France
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    699
  • Abstract
    Neural networks (NN) have been widely used in adaptive signal processing last decade. Their adaptive properties and nonlinear characteristics make them powerful tools to overcome difficult nonlinear problems. Satellite communications channels have nonlinear complex gain which makes the decision boundaries between different symbols nonlinear. NNs have been successfully used for satellite channel equalization. In this paper we present a multilayer neural network equalizer applied to UMTS channel equalization. We propose to use the natural gradient algorithm instead of the ordinary gradient in order to enhance the convergence properties of the NN
  • Keywords
    channel allocation; equalisers; gradient methods; mobile satellite communication; multilayer perceptrons; telecommunication computing; UMTS channel equalization; adaptive properties; adaptive signal processing; convergence properties; decision boundaries; multilayer neural network equalizer; natural gradient algorithm; nonlinear characteristics; nonlinear complex gain; satellite channel equalization; satellite communications channels; 3G mobile communication; Adaptive signal processing; Digital communication; Equalizers; Filters; High power amplifiers; Multi-layer neural network; Neural networks; Satellite communication; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.939109
  • Filename
    939109