Fast identification of amplitude modulated signals at low SNR

Modulation identification of communication signals has broad prospects in many fields. However, when the signal-to-noise ratio (SNR) is low, the identification of high-level amplitude modulated (M-QAM and M-ASK) signals is still challenging. This paper presents a method of fast identifying amplitude modulated signals using wavelet transform (WT) with an optimal scale. Only 100 symbols were used to acquire a high percentage of correct identification. Simulation shows when the SNR is not lower than -4 dB, the percentage of correct identification for M-QAM (M=16,64,128) is higher than 93%. When the SNR is not lower than -10 dB the percentage of correct identification for M-ASK (M=2,4,8) is higher than 90%. Simulation results show this present method is real-time and the performance is significantly improved in low SNR.