Theoretical Derivation of Minimum Mean Square Error of RBFbased Equalizer 


Vol. 31,  No. 8, pp. 795-800, Aug.  2006


PDF
  Abstract

In this paper, the minimum mean square error(MSE) convergence of the RBF equalizer is evaluated and compared with the linear equalizer based on the theoretical minimum MSE. The basic idea of comparing these two equalizers comes from the fact that the relationship between the hidden and output layers in the RBF equalizer is also linear. As extensive studies of this research, various channel models are selected, which include linearly separable channel, slightly distorted channel, and severely distorted channel models. In this work, the theoretical minimum MSE for both RBF and linear equalizers were computed, compared and the sensitivity of minimum MSE due to RBF center spreads was analyzed. It was found that RBF based equalizer always produced lower minimum MSE than linear equalizer, and that the minimum MSE value of RBF equalizer was obtained with the center spread which is relatively higher(approximately 2 to 10 times more) than variance of AWGN. This work provides an analytical framework for the practical training of RBF equalizer system.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

J. Lee, "Theoretical Derivation of Minimum Mean Square Error of RBFbased Equalizer," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 8, pp. 795-800, 2006. DOI: .

[ACM Style]

Jung-Sik Lee. 2006. Theoretical Derivation of Minimum Mean Square Error of RBFbased Equalizer. The Journal of Korean Institute of Communications and Information Sciences, 31, 8, (2006), 795-800. DOI: .

[KICS Style]

Jung-Sik Lee, "Theoretical Derivation of Minimum Mean Square Error of RBFbased Equalizer," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 8, pp. 795-800, 8. 2006.