A Symbol Rate Estimation Algorithm Based on Stochastic Resonance Combined with Wavelet Transform
ZHANG Zheng1, MA Jin-quan1,2
1. PLA Strategic Support Force Information Engineering University, Zhengzhou, Henan 450002, China;
2. National Signal Analysis & Processing Experiment Education Demonstration Center, Zhengzhou, Henan 450002, China
Abstract: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.
张政, 马金全. 一种随机共振联合小波变换的符号速率估计方法[J]. 电子学报, 2019, 47(12): 2647-2652.
ZHANG Zheng, MA Jin-quan. A Symbol Rate Estimation Algorithm Based on Stochastic Resonance Combined with Wavelet Transform. Acta Electronica Sinica, 2019, 47(12): 2647-2652.
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