NDLI: Automatic classification of combined analog and digital modulation schemes using feedforward neural network

Content Provider	IEEE Xplore Digital Library
Author	Popoola, J.J. van Olst, R.
Copyright Year	2011
Description	Author affiliation: School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa (Popoola, J.J.; van Olst, R.)
Abstract	This paper presents an artificial neural network based automatic modulation classifier system which can be used to classify combined analog and digital modulation schemes. Four best known analog modulation schemes and five corresponding digital modulation schemes were considered. An approach that involves three different steps in developing an automatic modulation classification is presented. The first step involves the extraction of the statistical feature keys used as the inputs to the classifier. The statistical feature keys are extracted from instantaneous amplitude, instantaneous frequency and phase of the simulated signals using MATLAB code. The second step involves the development of the automatic modulation classifier based on a backpropagation neural network algorithm. The third step of the methodology involves the performance evaluation of the developed automatic modulation classifier with a related study from the research literature. Results obtained show that the developed classifier is accurate and sensitive to classification of the nine modulation schemes considered with an average success rate above 99.0%.
Starting Page	1
Ending Page	6
File Size	714405
Page Count	6
File Format	PDF
ISBN	9781612849928
ISSN	21530033
e-ISBN	9781612849935
DOI	10.1109/AFRCON.2011.6072008
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-13
Publisher Place	Zambia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Classification algorithms Feature extraction Signal to noise ratio Frequency modulation Artificial neural networks automatic modulation classification artificial neural network (ANN) ANN classification network training
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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