A novel technique for automatic modulation classification and time-frequency analysis of digitally modulated signals

dc.contributor.author	Subbarao, Venkata M.	en
dc.contributor.author	Khasim, Sayedu Noorbasha	en
dc.contributor.author	Thati, Jagadeesh	en
dc.date.accessioned	2015-02-07T20:00:44Z
dc.date.available	2015-02-07T20:00:44Z
dc.date.issued	2015-02-07
dc.identifier.uri	http://hdl.handle.net/11400/5831
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://e-jst.teiath.gr/	en
dc.subject	Instantaneous Frequency
dc.subject	Bandwidth
dc.subject	Kurtosis
dc.subject	Modified S-Transform
dc.subject	Στιγμιαία Συχνότητα
dc.subject	Κύρτωση
dc.title	A novel technique for automatic modulation classification and time-frequency analysis of digitally modulated signals	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Electronics
heal.classification	Τεχνολογία
heal.classification	Ηλεκτρονική
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://zbw.eu/stw/descriptor/10455-2
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Ηλεκτρονική
heal.language	en
heal.access	free
heal.publicationDate	2012
heal.bibliographicCitation	Subbarao, V.M., Khasim, S.N. and Thati, J. (2012). A novel technique for automatic modulation classification and time-frequency analysis of digitally modulated signals. "e-Journal of Science & Technology". [Online] 7(5): 17-28. Available from: http://e-jst.teiath.gr/	en
heal.abstract	Automatic classification of analog and digital modulation signals plays an important role in communication application such as an intelligent demodulator, interference identification and monitoring. The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. This paper presents a new approach for automatic modulation classification for digitally modulated signals. This method utilizes a signal representation known as the modulation model. The modulation model provides a signal representation that is convenient for subsequent analysis, such as estimating modulation parameters. The modulation parameters to be estimated are the carrier frequency, modulation type, and bit rate. The modulation model is formed via autoregressive spectrum modeling. The modulation model uses the instantaneous frequency and bandwidth parameters as obtained from the roots of the autoregressive polynomial. This method is also classifies accurately under low carrier to noise ratio (CNR). This paper is also presents an improved version of S-Transform for time frequency analysis of different digitally modulated signals to observe variations of amplitude, frequency and phase.	en
heal.publisher	Νερατζής, Ηλίας	el
heal.publisher	Σιανούδης, Ιωάννης	el
heal.journalName	e-Journal of Science & Technology	en
heal.journalName	e-Περιοδικό Επιστήμης & Τεχνολογίας	el
heal.journalType	peer-reviewed
heal.fullTextAvailability	true