Online modulation recognition of analog communication signals using neural network

In this paper, a neural network based online analog modulation recognition of communication signals is presented. The proposed system can discriminate between amplitude modulation (AM), frequency modulation (FM), double sideband (DSB), upper sideband (USB), lower sideband (LSB) and continuous wave (...

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Bibliographic Details
Published in:Expert systems with applications 2007-07, Vol.33 (1), p.206-214
Main Authors: Guldemir, H., Sengur, A.
Format: Article
Language:English
Subjects:
Classification
Key features
Modulation
Neural network
Recognition
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Summary:In this paper, a neural network based online analog modulation recognition of communication signals is presented. The proposed system can discriminate between amplitude modulation (AM), frequency modulation (FM), double sideband (DSB), upper sideband (USB), lower sideband (LSB) and continuous wave (CW) modulations. A matlab graphical user interface (GUI) is designed to see the intercepted signal, its power spectral density, frequency and modulation type on the screen of the personnel computer. To achieve correct classification, extensive simulations have been done for training the neural network. Theoretical simulations and experimental results indicate good performance even at signal-to-noise ratios as low as 5 dB.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2006.04.015