Modulation classification using wavelet transform

Yu-Chuan Lin; C.-C. Jay Kuo

doi:10.1117/12.188776

11 October 1994 Modulation classification using wavelet transform

Yu-Chuan Lin, C.-C. Jay Kuo

Proceedings Volume 2303, Wavelet Applications in Signal and Image Processing II; (1994) https://doi.org/10.1117/12.188776
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

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.

Citation Download Citation

Yu-Chuan Lin and C.-C. Jay Kuo "Modulation classification using wavelet transform", Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); https://doi.org/10.1117/12.188776

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