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Improving accuracy in automatic modulation classification of digital modulated signals using design of experiment method

Improving accuracy in automatic modulation classification of digital modulated signals using design of experiment method / Chan Wui Hung

Abstract Klasifikasi modulasi automatik (AMC) merupakan sistem untuk mengklasifikasi format modulasi isyarat yang diterima. Ia merupakan system di antara penerima dan demodulator. Sistem ini penting kerana proses klasifikasi isyarat yang diterima mestilah boleh diharap supaya informasi yang diterima adalah tepat. Oleh itu, terdapat banyak penyelidikan telah dijalankan untuk mencari alternatif yang boleh meningkatkan ketepatan klasifikasi system AMC. Dalam projek ini, teknik persampelan tunda tak segerak (ADTS) telah dicadangkan dalam klasifikasi modulasi. Dengan menggunakan teknik ADTS, plot tunda kelewatan tak segerak (ADTP) yang unik dan berbeza telah dijana untuk setiap isyarat digital termodulat QPSK, 16-QAM dan 64- QAM. Data-data ini dibina semula untuk menjadi input kepada menyokong pengelas mesin vektor (SVM) yang terbina dalam MATLAB. Kaedah reka bentuk eksperimen (DoE) digunakan untuk meningkatkan ketepatan sistem AMC. Dalam DoE, reka bentuk factorial telah digunakan. Dua faktor yang dipilih ialah keterlambatan ketik dan tempoh persampilan yang digunakan dalam ADTS. Hasil klasifikasi mnunjukkan bahawa ketepatan pengelas adalah sebanyak 95.1%. Melalui DoE, ketepatan pengelas menggunakan nilai optimum ialah 97.6%. Keadaan ini menunjukkan peningkatan akurasi dalam system AMC apabila DoE digunakan. Sebagai kesimpulan, teknik-teknik yang dicadangkan mampu meningkatkan ketepatan system AMC. 2 2 _______________________________________________________________________________________________________ An automatic modulation classification (AMC) is a system is used to classify the modulation format of a received signal. It is a system placed in between the receiver and the demodulator. The AMC is crucial as the classification of received signal must be reliable to ensure the received information is correct. Therefore, a lot of studies had been conducted to look for the alternative for the improvement of classification accuracy of the AMC system. In this project, asynchronous delay tap sampling (ADTS) is proposed as a technique in modulation classification. From the ADTS, unique and distinct asynchronous delay tap plot (ADTP) is generated for each of the QPSK, 16-QAM and 64-QAM digital modulated signal. These data are then reconstructed to become the input of a built-in support vector machine (SVM) classifier in MATLAB. Design of experiment (DoE) method is applied to improve the accuracy of the AMC system. In DoE, 2 2 factorial design method is applied. The two selected factors are the delay tap and the sampling period used in ADTS. The results of the classification showed that the accuracy of the classifier is 95.1%. Through DoE, the accuracy of the classifier using the optimum values is 97.6%. This shows an improvement in the accuracy of the AMC system by using the DoE method. In conclusion, the proposed techniques are fully capable of improving the accuracy of the AMC system.

Contributor(s): Chan Wui Hung - Author Primary Item Type: Final Year Project Identifiers: Accession Number : 875007680 Language: English Subject Keywords: automatic modulation classification (AMC); system; signal First presented to the public: 6/1/2018 Original Publication Date: 8/10/2018 Previously Published By: Universiti Sains Malaysia Place Of Publication: School of Electrical & Electronic Engineering Citation: Extents: Number of Pages - 60 License Grantor / Date Granted:   / ( View License ) Date Deposited 2018-08-13 15:34:13.778 Date Last Updated 2019-01-07 11:24:32.9118 Submitter: Mohd Jasnizam Mohd Salleh

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