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An SNR unaware large margin automatic modulations classifier in variable SNR environments
Joint Authors
Zadah, Hamid Rida Husayn
Razzazi, Farbod
Source
The International Arab Journal of Information Technology
Issue
Vol. 14, Issue 5 (30 Sep. 2017)8 p.
Publisher
Publication Date
2017-09-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Automatic classification of modulation type in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military applications.
In this paper, a new two-stage partially supervised classification method is proposed for Additive White Gaussian Noise (AWGN) channels with unknown signal to noise ratios, in which a system adaptation to the environment Signal-to-Noise Ratios (SNR) and signals classification are combined.
System adaptation to the environment SNR enables us to construct a blind classifier to the SNR.
In the classification phase of this algorithm, a passive-aggressive online learning algorithm is applied to identify the modulation type of input signals.
Simulation results show that the accuracy of the proposed algorithm approaches to a welltrained system in the target SNR, even in low SNRs
American Psychological Association (APA)
Zadah, Hamid Rida Husayn& Razzazi, Farbod. 2017. An SNR unaware large margin automatic modulations classifier in variable SNR environments. The International Arab Journal of Information Technology،Vol. 14, no. 5.
https://search.emarefa.net/detail/BIM-852139
Modern Language Association (MLA)
Zadah, Hamid Rida Husayn& Razzazi, Farbod. An SNR unaware large margin automatic modulations classifier in variable SNR environments. The International Arab Journal of Information Technology Vol. 14, no. 5 (Sep. 2017).
https://search.emarefa.net/detail/BIM-852139
American Medical Association (AMA)
Zadah, Hamid Rida Husayn& Razzazi, Farbod. An SNR unaware large margin automatic modulations classifier in variable SNR environments. The International Arab Journal of Information Technology. 2017. Vol. 14, no. 5.
https://search.emarefa.net/detail/BIM-852139
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-852139