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Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method

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...

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Main Author: Chan, Wui Hung
Format: Monograph
Language:English
Published: Universiti Sains Malaysia 2018
Subjects:
T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Online Access:http://eprints.usm.my/53563/1/Improving%20Accuracy%20In%20Automatic%20Modulation%20Classification%20Of%20Digital%20Modulated%20Signals%20Using%20Design%20Of%20Experiment%20Method_Chan%20Wui%20Hung_E3_2018.pdf
http://eprints.usm.my/53563/
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spelling my.usm.eprints.53563 http://eprints.usm.my/53563/ Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method Chan, Wui Hung T Technology TK Electrical Engineering. Electronics. Nuclear Engineering 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, 22 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. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53563/1/Improving%20Accuracy%20In%20Automatic%20Modulation%20Classification%20Of%20Digital%20Modulated%20Signals%20Using%20Design%20Of%20Experiment%20Method_Chan%20Wui%20Hung_E3_2018.pdf Chan, Wui Hung (2018) Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted)
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
spellingShingle T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Chan, Wui Hung
Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
description 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, 22 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.
format Monograph
author Chan, Wui Hung
author_facet Chan, Wui Hung
author_sort Chan, Wui Hung
title Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
title_short Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
title_full Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
title_fullStr Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
title_full_unstemmed Improving Accuracy In Automatic Modulation Classification Of Digital Modulated Signals Using Design Of Experiment Method
title_sort improving accuracy in automatic modulation classification of digital modulated signals using design of experiment method
publisher Universiti Sains Malaysia
publishDate 2018
url http://eprints.usm.my/53563/1/Improving%20Accuracy%20In%20Automatic%20Modulation%20Classification%20Of%20Digital%20Modulated%20Signals%20Using%20Design%20Of%20Experiment%20Method_Chan%20Wui%20Hung_E3_2018.pdf
http://eprints.usm.my/53563/
_version_ 1739828995654942720
score 13.211869

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