Modulation Recognition of SDR Receivers Based on WNN

In this paper, a new effective method of digital modulation recognition is proposed to recognize different modulation types for software defined radio receivers, where an orthogonal wavelet-basis neural network approximator based on a multi-resolution analysis wavelet is training to be a modulation classifier under the condition of lower and wider range of SNR, which can work with the good performance of high robustness because of the insensitivity of the wavelet spectrum to the wide range of SNR of the signal, as well as without the local convergence resulting from non-liner optimization of the BP neural network classifier. To measure the performance of the proposed method, experiments are carried out to classify different types of band-limited modulated signals received by a software radio receiver and corrupted by AWGN. It is found that the overall success rate of the proposed method is over 98.61% at the SNR of 8 dB