Intelligent modulation type identification using GA-SVM based on WPA

Authors:
Ataollh Ebrahimzadeh;Seyed Alireza Seyedin
Affiliations:
Department of Electrical and Computer Engineering, Noshirvani Institute of Technology, Ferdowsi University of Mashad, Iran;Department of Electrical and Computer Engineering, Noshirvani Institute of Technology, Iran
Venue:
EC'06 Proceedings of the 7th WSEAS International Conference on Evolutionary Computing
Year:
2006

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Abstract

Automatic digital modulation identification through signal processing has found many applications such wireless communication system, nowadays. This paper proposes an Intelligent Digital Modulation Identifier (IDMI) that is new in this area. IDMI includes three main pats: wavelet packet analysis (WPA), support vector machines (SVM) and genetic algorithm (GA). WPA extracts features from received signal. SVM classifies according to extracted features. GA finds the best kernel parameter for SVM also does features selection. IDMTI is used to separate PSK2 and PSK4. Simulation result show IDMI has high performance comparable other methods even in low SNR.