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Proceedings Paper

Modulation classification using wavelet transform
Author(s): Yu-Chuan Lin; C.-C. Jay Kuo
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Paper Abstract

The wavelet transform has found applications in singularity classification/detection of signal waveforms. In this research, we apply the Morlet wavelet to detect the phase changes, and use the phase change rate as a feature for the classification of PSK modulation schemes. The likelihood function of the alphabet size with respect to the number of symbol change, which corresponds to the phase change of PSK signals, is derived by assuming that the transmitted symbol sequence is i.i.d. and equally likely distributed in an alphabet set. The classification problem can then be formulated as a likelihood ratio test by using the hypothesis testing technique. We show the performance of BPSK/QPSK and CW/BPSK classifiers in numerical experiments.

Paper Details

Date Published: 11 October 1994
PDF: 12 pages
Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); doi: 10.1117/12.188776
Show Author Affiliations
Yu-Chuan Lin, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 2303:
Wavelet Applications in Signal and Image Processing II
Andrew F. Laine; Michael A. Unser, Editor(s)

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