By Topic

Automatic classification of amplitude, frequency, and phase shift keyed signals in the Wavelet Domain

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ka Mun Ho ; Department of Electrical and Computer Engineering, Rutgers, the State University of New Jersey, 94 Brett Road, Piscataway, 08854, U.S.A. ; Canute Vaz ; David G. Daut

In this study, automatic recognition of digitally modulated signals is investigated using the Continuous Wavelet Transform (CWT) in conjunction with techniques typically used in pattern recognition. In particular, the method of template matching is used. The templates used for the Automatic Modulation Recognition (AMR) process are determined based on the features, i.e., fractal patterns in the scalograms, of specific modulation schemes as they appear in the Wavelet Domain (WD). The digital modulation schemes considered include both binary and quaternary Amplitude (ASK) and Frequency Shift Keying (FSK), as well as M-ary Phase Shift Keying (MPSK) signals, where M=2, 4, and 8. The modulated signals used in this study have been corrupted by Additive White Gaussian Noise (AWGN) resulting in Signal-to-Noise Ratios (SNRs) in the range of -5 dB to 10 dB. Through the use of Monte Carlo computer simulations, it has been determined that the average overall correct classification rate for M-ary PSK signals was 99.1%; 98.9% for BASK and 4-ASK signals; and 90.4% for BFSK and 4-FSK signals over the range of SNR values.

Published in:

Sarnoff Symposium, 2010 IEEE

Date of Conference:

12-14 April 2010