Kahsay, Tekleweyni (2014) Digital Modulation Identification and Modulation Orders Estimation Using Wavelet Transform. Masters thesis, Addis Ababa University.
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Abstract
Automatic modulation identification is rapidly evolving in many areas mainly in military applications and research institutions. The identification methods are basically categorized as likelihood based (LB) and feature based (FB) approaches. In this thesis FB is proposed to study modulation identification 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 identifies 13 modulation schemes 4 for FSK, 3 for QAM, 3 for ASK and 3 for PSK modulation types without prior knowledge. The correct identification ratio has been analyzed based on the confusion matrix for different modulation type at different signal to noise ratio (SNR) and the intra-class and inter-class identification of those modulation schemes are evaluted. The correct intra-class identification 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 identifies more modulation schemes compared to related exsiting works.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Feature based, Modulation identification, Wavelet and Histogram |
| Subjects: | H Social Sciences > HE Transportation and Communications Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Africana |
| Depositing User: | Andriamparany Edilbert RANOARIVONY |
| Date Deposited: | 10 Aug 2018 11:58 |
| Last Modified: | 10 Aug 2018 11:58 |
| URI: | http://thesisbank.jhia.ac.ke/id/eprint/8035 |
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