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Proceedings Paper

Wavelet-based communication channel modeling and identification
Author(s): Milos Doroslovacki; Ljubisa Stankovic
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Paper Abstract

The theory of modeling linear communication channels by wavelets is reviewed. It is shown that wavelet-based channel identification can converge fast and be a flexible tool for dealing with many different signal propagation situations. Moreover, wavelet-based identification can provide robustness against narrow band noise and/or impulse noise. Possibilities for sparse channel representations are emphasized and illustrated by real life examples. A wavelet packet decomposition that maximizes the convergence speed of the LMS algorithm used in channel identification is discussed. Comparisons with the DFT, DCT, and other transforms are given.

Paper Details

Date Published: 8 March 2002
PDF: 15 pages
Proc. SPIE 4738, Wavelet and Independent Component Analysis Applications IX, (8 March 2002); doi: 10.1117/12.458729
Show Author Affiliations
Milos Doroslovacki, George Washington Univ. (United States)
Ljubisa Stankovic, Univ. of Montenegro (Montenegro)

Published in SPIE Proceedings Vol. 4738:
Wavelet and Independent Component Analysis Applications IX
Harold H. Szu; James R. Buss, Editor(s)

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