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Distance Measure for Biased Probability Density Functions and Related Equalizer Algorithms for Non-Gaussian Noise
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 Title & Authors
Distance Measure for Biased Probability Density Functions and Related Equalizer Algorithms for Non-Gaussian Noise
Kim, Namyong;
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 Abstract
In this paper, a new distance measure for biased PDFs is proposed and a related equalizer algorithm is also derived for supervised adaptive equalization for multipath channels with impulsive and time-varying DC bias noise. From the simulation results in the non-Gaussian noise environments, the proposed algorithm has proven not only robust to impulsive noise but also to have the capability of cancelling time-varying DC bias noise effectively.
 Keywords
Distance measure;Biased;Probability density function;DC bias;impulsive noise;Supervised equalization;
 Language
English
 Cited by
 References
1.
L. M. Garth, "A dynamic convergence analysis of blind equalization algorithms," IEEE Trans. on Commun., vol. 49, pp. 624-634. Apr. 2001. crossref(new window)

2.
K. Blackard, T. Rappaport, and C. Bostian, "Measurements and models of radio frequency impulsive noise for indoor wireless communications," IEEE J. Select. Areas Commun., vol. 11, pp. 991-1001, Sept. 1993. crossref(new window)

3.
K. Koike and H. Ogiwara, "Application of Turbo TCM codes for impulsive noise channel," IEICE Trans. Fund. Electr., vol. E81-A, no. 10, pp. 2032-2039, Oct. 1998.

4.
M. Button, J. Gardiner, and I. Glover, "Measurement of the impulsive noise environment for satellite-mobile radio systems at 1.5 GHz," IEEE Trans. Veh. Technol.. vol. 51, no. 3, pp. 551-560, May 2002. crossref(new window)

5.
M. Richharia, Satellite communication systems: design principles, 2nd Ed. Palgrave Macmillan Limited, 1999.

6.
H. Sedarat, and K. Fishera, "Multicarrier communication in presence of biased-Gaussian noise sources," J. Signal Processing, vol. 88, issue 7, pp. 1627-1635, Jul. 2008. crossref(new window)

7.
J. Mazo, "Asymptotic distortion spectrum of clipped, dc-biased, Gaussian noise," IEEE Trans. Commun., vol. 40, no. 8, pp. 1339-1344, Aug. 1992. crossref(new window)

8.
J. Principe, D. Xu, and J. Fisher, "Information theoretic learning," in: S. Haykin, Unsupervised Adaptive Filtering, Wiley, New York, pp. 265-319, 2000.

9.
E. Parzen, "On the estimation of a probability density function and the mode," J. Ann. Math. Stat. vol. 33, issue 3, pp. 1065-1076, 1962. crossref(new window)

10.
K. Jeong, J. Xu, D. Erdogmus, and J. Principe, "A new classifier based on information theoretic learning with unlabeled data," Neural Networks, vol. 18, no. 5-6, pp. 719-726, 2005. crossref(new window)

11.
N. Kim, "Adaptive equalization using PDF matching algorithms for underwater communication channels with impulsive noise," J. KICS, vol. 36, no. 10, pp. 1210-1215, Oct. 2011.

12.
P. Delaney, "Signal detection in multivariate class A interference," IEEE Trans. Commun., vol. 43, no. 2/3/4, pp. 365-373, Feb/Mar./Apr. 1995. crossref(new window)