International Journal of Fuzzy Logic and Intelligent Systems

  • 제4권3호
  • /
  • Pages.259-265
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  • 2004
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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A New Hybrid Genetic Algorithm for Nonlinear Channel Blind Equalization

  • Han, Soowhan (Dept of Multimedia Engineering, Dongeui University) ;
  • Lee, Imgeun (Dept of Film & Visual Engineering, Dongeui University) ;
  • Han, Changwook (School of Electrical Eng. & Computer Science, Youngnam University)
  • 발행 : 2004.12.01
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초록

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

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참고문헌

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