NDLI: A novel approach for automatic classification of digitally modulated signals in HF communications

Content Provider	IEEE Xplore Digital Library
Author	Hazza, A. Shoaib, M. Saleh, A. Fahd, A.
Copyright Year	2010
Description	Author affiliation: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia (Hazza, A.; Saleh, A.; Fahd, A.) \|\| Prince Sultan Advanced Technologies Research Institute/STC-Chair, College of Engineering, King Saud University, Riyadh, Saudi Arabia (Shoaib, M.)
Abstract	In this paper, we propose a novel algorithm for automatic modulation classification of single carrier digital modulations widely used in High Frequency (HF) band that serves both military and civilian applications. Specifically, the proposed algorithm addresses the classification of 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, 64QAM, and OQPSK using two features: Dissimilarity in constellation diagram for classification of PSK/QAM signals and spectral peaks for classification of FSK signals with the use of both Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The robustness of proposed algorithm is tested against noise power and changes in noise model. Additive White Gaussian Noise (AWGN) and Bi-kappa noise models are considered in this work, as both exist in HF band.
Starting Page	271
Ending Page	276
File Size	1660887
Page Count	6
File Format	PDF
ISBN	9781424499922
e-ISBN	9781424499915
DOI	10.1109/ISSPIT.2010.5711793
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-15
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Frequency shift keying Signal to noise ratio AWGN Robustness Phase shift keying Quadrature amplitude modulation HF band Automatic modulation classification spectral peaks estmiation smoothing filter dissimilarity features Support vectore machine bi-kappa noise
Content Type	Text
Resource Type	Article

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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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