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Digital Modulation Identi cation and Modulation orders Estimation using Wavelet Transform

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dc.contributor.advisor Derebssa, Bisrat
dc.contributor.author Kahsay, Tekleweyni
dc.date.accessioned 2018-06-26T11:33:16Z
dc.date.available 2018-06-26T11:33:16Z
dc.date.issued 2014-10
dc.identifier.uri http://etd.aau.edu.et/handle/123456789/3719
dc.description.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 en_US
dc.language.iso en en_US
dc.publisher Addis Ababa University en_US
dc.subject Feature based en_US
dc.subject Modulation identifcation en_US
dc.subject Wavelet and Histogram en_US
dc.title Digital Modulation Identi cation and Modulation orders Estimation using Wavelet Transform en_US
dc.type Thesis en_US


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