Genetic Programming for Channel Equalisation   [GP]

by

Esparcia­Alcazar, A., Esparcia-Alcazar, A. and Sharman, K.

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Info: Evolutionary Image Analysis, Signal Processing and Telecommunications: First European Workshop, EvoIASP'99 and EuroEcTel'99 (Conference proceedings), 1999, p. 126-137
Keywords:genetic algorithms, genetic programming
Abstract:
This paper is devoted to providing a comparison between classical and neural channel equalisation techniques and node gain Genetic Programming enhanced [GP] with Simulated Annealing [SA] (or GP+SA). Firstly, the shortcomings of existing techniques are exposed and the main requirements to demand of a new method enumerated. A description of the problem is followed by an account of particular cases of equalisation, exemplified by three channels, both linear and nonlinear. Results are obtained for these channels both with the proposed method and a classical technique, the Recursive Least Squares [LS] (RLS) algorithm, and they are further compared to those existing in the literature. The comparison shows the great potential of GP+SA, especially in the case of nonlinear channels. The main disadvantage of the proposed method, the computational effort [CE] involved, is also pointed out and it is concluded that, upon the whole, the method deserves further investigation.
Notes:
EvoIASP99'99
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BibTex:
@InProceedings{esparcia­alcazar:1999:GPce,
  author =       "Anna Esparcia­Alcazar and Ken Sharman",
  title =        "Genetic Programming for Channel Equalisation",
  booktitle =    "Evolutionary Image Analysis, Signal Processing and
                 Telecommunications: First European Workshop, EvoIASP'99
                 and EuroEcTel'99",
  year =         "1999",
  editor =       "Riccardo Poli and Hans-Michael Voigt and Stefano
                 Cagnoni and Dave Corne and George D. Smith and Terence
                 C. Fogarty",
  volume =       "1596",
  series =       "LNCS",
  pages =        "126--137",
  address =      "Goteborg, Sweden",
  publisher_address = "Berlin",
  month =        "28-29 " # may,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-65837-8",
  URL =          "http://www.springer.de/cgi-bin/search_book.pl?isbn=3-540-65837-8",
  abstract =     "This paper is devoted to providing a comparison
                 between classical and neural channel equalisation
                 techniques and node gain Genetic Programming enhanced
                 with Simulated Annealing (or GP+SA). Firstly, the
                 shortcomings of existing techniques are exposed and the
                 main requirements to demand of a new method enumerated.
                 A description of the problem is followed by an account
                 of particular cases of equalisation, exemplified by
                 three channels, both linear and nonlinear. Results are
                 obtained for these channels both with the proposed
                 method and a classical technique, the Recursive Least
                 Squares (RLS) algorithm, and they are further compared
                 to those existing in the literature. The comparison
                 shows the great potential of GP+SA, especially in the
                 case of nonlinear channels. The main disadvantage of
                 the proposed method, the computational effort involved,
                 is also pointed out and it is concluded that, upon the
                 whole, the method deserves further investigation.",
  notes =        "EvoIASP99'99",
}