In this paper, we propose a recursive sparse channel estimation algorithm in the presence of impulse noise. Firstly the channel impulse response and impulsive noise are jointly viewed as an unknown sparse vector. Then a novel recursive Kalman filtering based compressed sensing algorithm for joint channel and impulsive noise estimation is proposed by using the first order autoregressive model for tracking slowly time varying wireless channel. This algorithm can be extended also to quasi-static, block-fading scenario conveniently. Simulation results illustrate the efficiency of the proposed techniques in terms of the mean square error and bit error rate performance.

中文翻译：

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基于卡尔曼滤波器的OFDM系统脉冲噪声环境中慢衰落稀疏信道的递归估计

在本文中，我们提出了一种存在脉冲噪声的递归稀疏信道估计算法。首先，信道脉冲响应和脉冲噪声被共同视为一个未知的稀疏向量。然后利用一阶自回归模型跟踪慢时变无线信道，提出了一种新的基于递归卡尔曼滤波的压缩感知联合信道和脉冲噪声估计算法。该算法还可以方便地扩展到准静态、块衰落场景。仿真结果说明了所提出的技术在均方误差和误码率性能方面的效率。