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A new digital modulation recognition algorithm based on the instantaneous information is proposed to improve the recognition success rate in the low signal noise ratio (SNR). First denoising of the instantaneous information is optimized by wavelet filter, which can improve the recognition ability at low SNR. Besides the existing 3 key feature parameters, 3 new key feature parameters are proposed to be used as the decision criteria for identifying different types of digital modulation, which simplifies the recognition process and improves the recognition ability at low SNR. The simulations demonstrate that all modulation types of interest have been classified with success rate of no lower than 99 % when SNR is 10dB. Even if the SNR is lower than 5 dB, the success rate is over 95.4 % for most of the modulation types.
A new digital modulation recognition algorithm based on the instantaneous information is proposed to improve the recognition success rate in the low signal noise ratio (SNR). First denoising of the instantaneous information is optimized by wavelet filter, which can improve the recognition ability at low SNR . The existing 3 key feature parameters, 3 new key feature parameters are proposed to be used as the decision criteria for identifying different types of digital modulation, which simplifies the recognition process and improves the recognition ability at low SNR. The simulations demonstrate that all Even if the SNR is lower than 5 dB, the success rate is over 95.4% for most of the modulation types.