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A Study of Signal Modulation Recognition Based on Wavelet Analysis and Random Forest

Nowadays, the recognition of signal modulation mode has received tremendous attention for its indispensable role in both military and civilian fields. With several typical types of modulation signals generated, a signal recognition method based on wavelet analysis and the random forest is proposed. Afterward, to reduce the time and space complexity of the algorithm, redundant features were eliminated by correlation analysis. By adopting a decision tree and random forest algorithm, the modulation recognition accuracies of the signals are calculated and analyzed. Finally, under different signal-noise ratios, a further study is carried out about the effects that wavelet autocorrelation denoising and wavelet soft-threshold denoising have on the recognition accuracy of Random Forest.