Modulation recognition of communication signal based on wavelet RBF neural network

Abstract

Modulation recognition of communication signal is to confirm the modulation style of communication signal in the condition with much noise. Wavelet transformation has a good localization characteristic in time-frequency domain, while the neural network has characteristics of self-studying, self-adaptation, and high stabilization and can improve the autoimmunization and intelligence of recognition. We adopted the ideal of combination of wavelet and neural network in the paper, firstly, we used the wavelet to decompose the signal, and then abstracted the characteristic through the wavelet coefficient, lastly we adopted the RBF(Radial Basis Funtion) nerual network to recognize 4 kinds of common digital communication signal. The simulation results indicate that the presented method performs well.