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Proceedings Paper

Conjugate-gradient-based decision feedback equalization with structured channel estimation for digital Television
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Paper Abstract

In this paper, we show how the convergence time of equalizers for 8-VSB based on the conjugate gradient (CG) algorithm can be considerably improved through initialization based on a channel estimate. We derive real and complex minimum mean-square error (MMSE) equalizers and implement them adaptively using the conjugate gradient, recursive least squares (RLS), and least mean squares (LMS) algorithms. We show that both CG and RLS have similar convergence times --- both are much faster than LMS. Since the CG algorithm is easily initialized, we compare several methods of initialization to determine how each affects convergence and then apply the best methods to initialize equalizers using channel estimates. We find that initializing the correlation matrices and filling the feedback taps with training symbols greatly speeds convergence of the CG adaptive equalizer, potentially approaching the rate of convergence when running the algorithm on the matrix equations using the actual channel.

Paper Details

Date Published: 25 June 2002
PDF: 11 pages
Proc. SPIE 4740, Digital Wireless Communications IV, (25 June 2002);
Show Author Affiliations
Michael D. Zoltowski, Purdue Univ. (United States)
William J. Hillery, Purdue Univ. (United States)
Serdar Ozen, Purdue Univ. (United States)
Mark Fimoff, Zenith Electronics Corp. (United States)

Published in SPIE Proceedings Vol. 4740:
Digital Wireless Communications IV
Raghuveer M. Rao; Soheil A. Dianat; Michael D. Zoltowski, Editor(s)

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