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 thier 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 identi cation,Wavelet
and Histogram
Description
Keywords
Feature based, Modulation identifcation, Wavelet and Histogram