Convergence Analysis of a Prediction based Adaptive Equalizer for IIR Channels
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Convergence Analysis of a Prediction based Adaptive Equalizer for IIR Channels

Authors: Miloje S. Radenkovic, Tamal Bose

Abstract:

This paper presents the convergence analysis of a prediction based blind equalizer for IIR channels. Predictor parameters are estimated by using the recursive least squares algorithm. It is shown that the prediction error converges almost surely (a.s.) toward a scalar multiple of the unknown input symbol sequence. It is also proved that the convergence rate of the parameter estimation error is of the same order as that in the iterated logarithm law.

Keywords: Adaptive blind equalizer, Recursive leastsquares, Adaptive Filtering, Convergence analysis.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328860

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[1] D. N. Godard, "Self recovering equalization and carrier tracking in the two dimensional data communication systems," IEEE Trans. Commun., vol. COMM-28, pp. 1867-1875, November 1980.
[2] O. Shalvi and E. Weinstein, "New criterion for blind deconvolution of minimum phase system (channels)," IEEE Trans. Inform. Theory, vol. 36, pp. 312-321, March 1990.
[3] C. R. Johnson, P. Schniter, T. J. Endres, J. D. Behm, D. R. Brown and R. A. Casas, "Blind equalization using the constant modulus criterion: a review," Proc. of the IEEE, vol. 86, no. 10, pp. 1927- 1949, Oct. 1998.
[4] L. Toug, G. Xu and T. Kailath, "Blind identification and equalization based on a second order statics: a time domain approach," IEEE Trans. Inform. Theory, vol. 40, pp.340-349, March 1994.
[5] E. W. Bai and M. Fu, "Blind system identification and channel equalization of IIR system without statistical information," IEEE Trans. Signal Processing, vol. 47, pp. 1910-1920, July 1999.
[6] D. Gesbert and P. Duhamel, "Unbiased blind adaptive channel identification and equalization," IEEE Trans. Signal Processing, vol. 48, pp.148-158, Jan. 2000.
[7] L. Tong and S. Perrean, "Multichannel blind identification: from subspace to maximum likelihood methods," Proc. IEEE, vol. 86, no. 10, pp.1951-1968, 1998.
[8] K. Abed-Meriau, E. Mouliues and P. Loubaton "Prediction error method for second-order blind identification," IEEE Trans. Signal Processing, vol. 45, pp. 694-705, 1997.
[9] J. Tugnait, "Multistage linear prediction based blind equalization of FIR/IIR single-input multiple-output channels with common zeros," IEEE Trans. Signal Processing, vol. 47, pp. 1689-1700, 1999.
[10] S. Haykin, "Adaptice Filter Theory," Prentice Hall, 2002.
[11] Y. S. Chow and H. Teicher, "Probability theory, indepdedence, interchangibility, martingles," Springer-Verlag, New York, 1978.