In non-cooperative communications

due to the deterioration of the channel

the Signal-Noise Ratio (SNR) of the receiving signal is very low in many cases

resulting in the inability to accurately estimate the symbol rate. Stochastic resonance can use noise energy to transfer and amplify the weak signals to some extent

and wavelet transform can effectively detect the instantaneous variation of phase and amplitude of the signals. By using the advantages of both methods

a combination algorithm for estimating the symbol rate of MPSK and MQAM is proposed. First

the adaptive parameter-tuning stochastic resonance is used to match the optimal system parameters for noisy signals

and then the transient information is further extracted by Haar wavelet transform

which not only compensates for the shortcomings of the poor effect of using stochastic resonance alone and its easy divergence as a non-linear system

but also reduce the influence of the optimal scale of the wavelet. The simulation result shows that this method can improve the output peak and reduce the SNR threshold

which is suitable for the symbol rate estimation under low SNR.