Digital Modulation Identi cation and Modulation orders Estimation using Wavelet Transform
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Date
2014-10
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Addis Ababa University
Abstract
Automatic modulation identication is rapidly evolving in many areas mainly in military applications and research institutions. The identication methods are basically categorized as likelihood based (LB) and feature based (FB) approaches. In this thesis FB is proposed to study modulation identication of received signals in the presence of additive white Gaussian noise (AWGN) using wavelets. The Haar wavelet was used as the mother wavelet. The algorithm identies 13 modu- lation schemes 4 for FSK, 3 for QAM, 3 for ASK and 3 for PSK modulation types without prior knowledge. The correct identi cation ratio has been analyzed based on the confusion matrix for di erent modulation type at di erent signal to noise ratio (SNR) and the intra-class and inter-class identi cation of those modulation schemes are evaluted. The correct intra-class identi cation ratio was greater than 99%, 97%, 96% and 83% at their lowerest SNR bounds 5dB, 8dB, 8dB and 25dB for FSK, QAM, ASK and PSK modulations respectively. The proposed method is relatively robust for noisy signal and identies more modulation schemes com- pared to related exsiting works. Key words: Feature based, Modulation identication,Wavelet and Histogram
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Feature based, Modulation identifcation, Wavelet and Histogram