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Parallel structure for sparse impulse response using moving window integration

机译：使用移动窗口积分的并行结构，用于稀疏脉冲响应

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摘要

A novel scheme is proposed to locate the dispersive region, whose location is essential for parallel echo cancellation. In the scheme, a first filter adapts to a subsampled version of the input signal to roughly identify the impulse response. After each adaptation, a squaring function and a moving window integration procedure are performed on the first filter, and the region with the maximum integration value is considered to be the dispersive region. Finally, a second short filter is used to precisely identify the active coefficients belonging to the located dispersive region to implement the actual echo cancellation. Simulation results suggest that the parallel structure improves its convergence speed 3 times and its computation can be reduced by 3/8 compared with the traditional NLMS algorithm by decreasing the filter length. Due to the more accurate estimate of the location, the misalignment noise of the proposed algorithm is at least 10 dB lower than that of the conventional dispersive region locating algorithm. Moreover, the proposed algorithm based on the parallel structure outperforms other sparse adaptive algorithms in all aspects.
机译：提出了一种新颖的方案来定位色散区域，该色散区域的位置对于并行回声消除是必不可少的。在该方案中，第一滤波器适应输入信号的二次采样版本，以大致识别脉冲响应。每次适应后，对第一滤波器执行平方函数和移动窗口积分过程，将积分值最大的区域视为色散区域。最后，第二个短滤波器用于精确地识别属于所定位的色散区域的有源系数，以实现实际的回声消除。仿真结果表明，与传统的NLMS算法相比，该并行结构通过减小滤波器长度将其收敛速度提高了3倍，并且计算量可减少3/8。由于对位置的估计更加准确，因此所提出算法的失准噪声比常规分散区域定位算法的失准噪声至少低10 dB。此外，所提出的基于并行结构的算法在所有方面都优于其他稀疏自适应算法。

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