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Nonlinear Bitwise Equalization

  • F. -J. González Serrano
  • M. Martínez Ramón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3124)

Abstract

A new family of nonlinear equalizers that detect Quadrature Amplitude Modulated (QAM) signals by decomposing the process into a binary decision “cascade” is proposed. First, the quadrant of the symbol is determined; second, we determine which quarter of the chosen quadrant contains our symbol, and so on. We have used two nonlinear architectures to approximate the optimal decision boundaries: a Volterra filter and a Generalized Cerebellar Model Arithmetic Computer. Our analysis demonstrates that bitwise equalizers achieve lower Bit Error Rate (BER) than transversal ones.

Keywords

Finite Impulse Response Quadrature Amplitude Modulate Cerebellar Model Articulation Controller Committee Machine Volterra Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    González-Serrano, F.J., Artés-Rodríguez, A., Figueiras-Vidal, A.R.: Generalizing CMAC Architecture and Training. IEEE Transactions on Neural Networks 9(6) (1998)Google Scholar
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    Saleh, A.A.M.: Frequency-Independent and Frequency-Dependent Nonlinear Models of TWT Amplifiers. IEEE Trans. on Communications COM-29(11), 1715–1720 (1981)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • F. -J. González Serrano
    • 1
  • M. Martínez Ramón
    • 1
  1. 1.Departamento de Teoría de la Señal y ComunicacionesUniversidad Carlos III de MadridLeganésSPAIN

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