Research On Key Technologies Of Blind Demodulation For MQAM Signal Under Impulse Noise

The quadrature amplitude modulation blind demodulation technology based on Gaussian noise has been studied for a long time.Most of the existing algorithms are based on the Gaussian model,and the signal characteristics are extracted by calculating the high-order statistics of the signal and then,used in the various steps of demodulation.However,in the actual communication system,various interference are encountered in the signal transmission process,and the noise tend to exhibit strong pulse characteristics.Higher-order moment of the signal under the impulse noise would further increase the influence of the noise,thereby degrading the performance of the algorithm,even completely invalid.Therefore,the research on blind demodulation of MQAM signal based on impulse noise is more practical.In this paper,we focus on the blind parameter estimation and blind equalization algorithm of MQAM signal under impulse noise.While suppressing impulse noise,the performance of blind parameter estimation and blind equalization algorithm is further improved.The main work of the article is as follows:(1)Aiming at the problem that the traditional cyclic spectrum estimation algorithm can not suppress the impulse noise,a carrier frequency and symbol rate estimation algorithm based on fractional lower moments is proposed.Simulation experiments show that the proposed algorithm effectively suppresses impulse noise and achieves joint estimation of carrier frequency and symbol rate.(2)Aiming at the problem of poor accuracy of the symbol rate estimation algorithm for MQAM signals under impulse noise,a symbol rate estimation algorithm based on recursive hybrid Myriad filter quadratic wavelet transform is proposed.Experimental verification shows that the algorithm further improves the accuracy of symbol rate estimation.(3)Aiming at the problem of poor convergence accuracy of traditional equalization algorithm under impulse noise,an improved FLOM-CMA algorithm is proposed firstly.Based on this,a variable step size improved FLOM-CMA algorithm based on Lorentzian function is proposed.The convergence accuracy of the equalization is further improved while suppressing the impulse noise.The performance of the algorithm is analyzed by simulation experiments,and the effectiveness of the algorithm is verified by actual data.(4)Aiming at the problem that for the single improved blind equalization algorithm,the convergence speed and accuracy cannot be satisfied at the same time,the improved FLOM-CMA algorithm and DD-LMP algorithm are convexly combined,and a current dual-mode blind equalization algorithm based on convex combination isproposed.The algorithm was verified by using simulation data and actual data respectively.The results show that the proposed algorithm can not only effectively suppress the impulse noise,but also achieve higher precision blind equalization under the condition that the convergence speed is not significantly increasing.