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A practical radial basis function equalizer.

J Lee1, C Beach, N Tepedelenlioglu

  • 1Department of Telecommunications Engineering, Kunsan National University, 68 Miryong-dong, Kunsan, Chonbuk, Korea.

IEEE Transactions on Neural Networks
|February 7, 2008
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Summary

A novel radial basis function (RBF) equalizer design significantly reduces the number of centers. This optimized RBF equalizer matches performance of traditional RBFs and surpasses conventional linear equalizers.

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Area of Science:

  • Signal Processing
  • Machine Learning
  • Communications Engineering

Background:

  • Radial Basis Function (RBF) equalizers offer advantages in non-linear channel equalization.
  • Conventional RBF equalizer design requires a large number of basis function centers, increasing computational complexity.
  • Efficient design of RBF equalizers is crucial for practical applications in digital communications.

Purpose of the Study:

  • To develop a novel design process for radial basis function (RBF) equalizers that substantially reduces the number of basis function centers.
  • To improve the efficiency and reduce the computational load of RBF equalizers without compromising performance.
  • To demonstrate the effectiveness of the proposed RBF equalizer design through simulation studies.

Main Methods:

  • A two-step algorithm for reducing the number of RBF centers: 1) selecting centers near the decision boundary, and 2) grouping and averaging selected centers.
  • Estimation of channel order and delay using regression analysis to determine initial center requirements.
  • Performance evaluation through simulation comparing the reduced-center RBF equalizer against a conventional RBF equalizer and a linear equalizer.

Main Results:

  • Achieved a reduction in RBF centers by a factor of over 2000-to-1.
  • The reduced-center RBF equalizer demonstrated performance comparable to the unreduced RBF equalizer.
  • The proposed RBF equalizer significantly outperformed conventional linear equalizers in simulations.

Conclusions:

  • The developed RBF equalizer design process effectively reduces the number of basis function centers while maintaining high performance.
  • This method offers a computationally efficient alternative to traditional RBF equalizers.
  • The optimized RBF equalizer presents a superior solution for channel equalization compared to conventional linear methods.