Type of Document	Master's Thesis
Author	Price, Matthew
URN	etd-05032011-103859
Title	Automatic Modulation Classification Using Grey Relational Analysis
Degree	Master of Science
Department	Electrical and Computer Engineering
Advisory Committee	Advisor Name Title Reed, Jeffrey Hugh Committee Chair Amanna, Ashwin E. Committee Member Bose, Tamal Committee Member
Keywords	Grey Relational Analysis Automatic Modulation Classification Haar Wavelet Transform Cumulants Cyclostationary Analysis
Date of Defense	2011-04-25
Availability	restricted
Abstract One component of wireless communications of increasing necessity in both civilian and military applications is the process of automatic modulation classification. Modulation of a detected signal of unknown origin requiring interpretation must first be determined before the signal can be demodulated. This thesis presents a novel architecture for a modulation classifier that determines the most likely modulation using Grey Relational Analysis with the extraction and combination of multiple signal features. An evaluation of data preprocessing methods is conducted and performance of the classifier is investigated with the addition of each new signal feature used for classification.
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