Digital signal modulation recognition method based on high-order cumulants and wavelet transform

Abstract

In view of the current situation that the recognition rate of digital signal modulation recognition method is unsatisfactory at low Signal-to-Noise Ratio(SNR), a recognition method based on high-order cumulants and wavelet transform is proposed to realize the automatic modulation recognition of 8 kinds of digital signals such as 2ASK, 4ASK, 8ASK, 2PSK, 4PSK, 8PSK, 16QAM and 32QAM. Based on the high-order cumulants principle and wavelet transform theory, the characteristic parameters f1∼f5 are constructed by the elaborate analysis of the characteristic extraction of these signals. Through simulation experiments, the characteristic parameter changes of different types of modulation signals at different SNR are obtained, and design the classifier of Back Propagation (BP) neural network to classify the signals. The simulation results show that this method can improve the average correct recognition rates of 8 digital modulation signals reaching up to above 97% when the SNR is higher than 0dB, which greatly improves the signal recognition performance at low SNR.