Abstract
Modulation type is one of the most important characteristics used in signal recognition. An algorithm to realize signal modulation identification is proposed in this paper. We applied wavelet transformation and STFT to the signal, and then used manifold learning method to reduce the high dimension and extracted the recognition feature. The proper threshold value was set as the classifier to achieve the purpose of recognizing 4 kinds of signals (MASK, MFSK, MPSK,QAM) in Gauss white noise environment. The algorithm requires priori signal information no other than signal-to-noise rate. Simulation result indicates the algorithm achieves good performance.
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