基于可动形状滤波器的数字自干扰消除算法

Haolong Wu, Yuwen Wang, Xuanrui Qu
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引用次数: 0

摘要

在数字自推理对消领域,自适应滤波器是消除自干扰的主要方法。为了优化自适应算法的性能,进行了大量的研究。然而,我们注意到很少有学者通过修改滤波器的形状来达到更好的对消效果。典型的自适应滤波器受到固定和不可移动形状的限制,不能充分利用数字信号背后的信息。在这个问题的激励下,为了获得更灵活的滤波器形状,人们做了大量的工作。本文提出了一种新的滤波器结构,称为可动形状滤波器。通过在典型滤波器中加入位置参数,可以获得较好的消噪效果。此外,严格的仿真结果表明,均方误差有了很大的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital Self-interference Cancellation Algorithm Based on The Movable Shape Filter
In digital self-inference cancellation field, the adaptive filter is the main way to eliminate self-interference. A mass of research is completed to optimize the performance of the adaptive algorithm. Nevertheless, we have noticed there are few scholars to modify the shape of the filter to achieve a better cancellation effect. Constrained by the fixed and immovable shape, the typical adaptive filter can't full use the information behind the digital signal. Stimulated by this problem, a lot of work have been fulfilled in order to acquire a more flexible filter shape. In this paper, we propose a novel filter architecture named as the movable shape filter. Through adding the position parameters to the typical filter, finer elimination results have been reached. Moreover, the rigorous simulation results show a great progress in the mean square error.
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