https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/cmu2.12165

Adaptive blind equalization of fast time‐varying channel with frequency estimation in impulsive noise environment

The prior information of impulsive noise at receiver will improve the performance of the communication systems impaired by impulsive noise. Therefore, parameters estimation techniques of Bernoulli-Gaussian noise are studied in this letter. A Fractional Order absolute Moment-based Estimator (FOME) is proposed and the Asymptotic Normalized Mean Square Error (ANMSE) of the FOME is derived. Both the ANMSE and simulation results show that the FOME performs better than the 1,2,3-order moment-based estimator, and the performance of the FOME will approach the expectation maximization estimator with the increase of the received signal length. 

Parameter Estimation of Bernoulli-Gaussian Noise Using Fractional Order Absolute Moments

A maximum correntropy criterion-blind clustering multi-modulus algorithm (MCC-BCMMA) is proposed to equalize multi-level quadrature amplitude modulation (QAM) channels in impulsive noise environment. The novel cost function is based on the maximum correntropy criterion (MCC), theoretical analysis shows that this criterion is useful when the noise is impulsive. Moreover, this cost function is decomposed into in-phase term and orthogonal term to eliminate the phase ambiguity, treats high-order QAM signal to classical QAM4 signal to reduce the error, and calculates the weight coefficients by a simple way. Simulation results show that the newly proposed algorithm MCC-BCMMA can be used to equalize multi-level QAM signals in both Gaussian and impulsive noise environments, and it shows better equalization performance under impulsive noise. The relationship between the kernel size of MCC, the convergence speed and accuracy is also analysed. 

Adaptive blind equalization for multi-level QAM signals in impulsive noise environment

The prior information of impulsive noise at receiver will improve the performance of the communication systems impaired by impulsive noise. Therefore, parameters estimation techniques of Bernoulli-Gaussian noise are studied in this letter. A Fractional Order absolute Moment-based Estimator (FOME) is proposed and the Asymptotic Normalized Mean Square Error (ANMSE) of the FOME is derived. Both the ANMSE and simulation results show that the FOME performs better than the 1,2,3-order moment-based estimator, and the performance of the FOME will approach the expectation maximization estimator with the increase of the received signal length.

Mao-Ching Chiu

Papers

Parameter estimation of impulsive noise for channel coded communication systems