A network of adaptive Kalman filters for data channel equalization
A network of adaptive Kalman filters for data channel equalization
复制标题
用于数据通道均衡的自适应卡尔曼滤波器网络
DOI：
10.1109/78.863067
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发表时间：
2000
影响因子：
5.4
通讯作者：
S. Marcos
中科院分区：
文献类型：
--
作者：
S. Marcos
本文的目的是重新审视基于卡尔曼滤波的信道均衡方法。实际上，卡尔曼均衡器已经在文献中被提出作为更经典结构的替代。然而，这些卡尔曼解决方案是基于高斯信号的假设，这在数据信道均衡的上下文中是无效的。从近似的数据信号的密度函数的高斯概率密度函数的加权和，我们在这里提出了一种新的结构的均衡器，是基于网络的卡尔曼滤波器并行操作。研究了该网络的自适应版本。它包括信道和噪声方差的在线估计。
The aim of this paper is to revisit the Kalman filtering-based approach of channel equalization. Indeed, Kalman equalizers have already been proposed in the literature as an alternative to more classical structures. However, these Kalman solutions are based on the assumption of Gaussian signals that is not valid in the context of data channel equalization. From an approximation of the density functions of the data signals by a weighted sum of Gaussian probability density functions, we here propose a new structure of an equalizer that is based on a network of Kalman filters operating in parallel. An adaptive version of this network is investigated. It includes the on-line estimation of the channel and of the noise variance.