An Efficient Method for Automatic Digital Modulation Classification in Fading Channels
Ataollah Ebrahimzadeh, Hamed Azimi
Journal of Networking Technology, Vol. 1, No. 1, 2010.
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Abstract:
Automatic digital modulation classification has seen under increasing demands, nowadays. It plays an important role for network traffic administration, different data rate allocation, signal confirmation, interference identification, software radios, multi-drop networks, intelligent modems, etc. In this paper we present a high efficient method that automatically classifies the digital modulations in dispersive channels. In this recognizer, a radial basis neural network is proposed as the classifier. Channel effects are mitigated using an equalizer. A combination set of the spectral features and the higher order moments up to eighth and the higher order cumulants up to eighth are proposed as the effective features. Simulation results show that the proposed classifier has high recognition accuracy at low level of the signal to noise ratios (SNRs).