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为了提高加性脉冲噪声衰落信道环境下的通信传输性能,提出了一种适用于对称稳定分布噪声的基于Kalman滤波的迭代信道估计方法。该方法利用时变信道的先验统计信息将信道建模为一阶自回归模型,并将最小分散系数准则应用于Kalman滤波信道估计方法中,从而更充分地利用了时变信道和非高斯噪声的先验信息。在较为严重的时变脉冲信道下,该方法比最小平均p范数估计方法性能要优约2 dB。仿真结果表明:该方法能消除脉冲噪声和稳定分布二阶矩不存在等不利因素的影响,能快速准确地跟踪并预测时变信道的变化,且性能显著地优于传统的最小均方误差和最小平均p范数信道估计方法。
In order to improve the performance of communication transmission in additive impulse noise fading channels, an iterative channel estimation method based on Kalman filtering is proposed for symmetric stable distribution noise. The method uses the prior statistical information of the time-varying channel to model the channel as a first-order autoregressive model and applies the minimum dispersion coefficient criterion to the Kalman filter channel estimation method to make better use of time-varying channel and non-Gaussian noise A priori information. Under the more severe time-varying impulse channel, this method is about 2 dB better than the minimum average p-norm estimation method. The simulation results show that the proposed method can eliminate the influence of impulsive noise and non-existence of second order moment of stable distribution, and can track and predict the time-varying channel changes quickly and accurately with better performance than the traditional minimum mean square error The least average p-norm channel estimation method.