An effective algorithm for automatic modulation recognition

Based on the previous studies, this article proposes an effective modulation recognition algorithm which is a combination of Higher Order Cumulants (HOC) and Continues Wavelet Transform (CWT). In the Additive White Gaussian Noise (AWGN) the identification of QAM16, QAM32, QAM64, BPSK, QPSK and PSK8 types of modulation were almost successful. In the case of the signal-to-noise ratio (SNR) was higher than -7dB, the identification of QAM16, QAM32 and QAM64 modulation types were 100% successful. While SNR was higher than -2dB, BPSK, QPSK and PSK8 modulation types were identified with success percentage of 100%, 98% and 99%, respectively.