Digital Modulation Identi cation and Modulation orders Estimation using Wavelet Transform

dc.contributor.advisorDerebssa, Bisrat
dc.contributor.authorKahsay, Tekleweyni
dc.date.accessioned2018-06-26T11:33:16Z
dc.date.accessioned2023-11-28T14:09:06Z
dc.date.available2018-06-26T11:33:16Z
dc.date.available2023-11-28T14:09:06Z
dc.date.issued2014-10
dc.description.abstractAutomatic 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 Histogramen_US
dc.identifier.urihttp://etd.aau.edu.et/handle/12345678/3719
dc.language.isoenen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectFeature baseden_US
dc.subjectModulation identifcationen_US
dc.subjectWavelet and Histogramen_US
dc.titleDigital Modulation Identi cation and Modulation orders Estimation using Wavelet Transformen_US
dc.typeThesisen_US

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