Linear equalization via factor graphs

R. Drost, A. Singer
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引用次数: 3

Abstract

This paper apply the factor graph framework to the techniques of linear equalization and decision feedback equalization to obtain a new class of low complexity equalization algorithms. The estimation of Gaussian processes has been studied in previous work, and the application of factor graphs to this problem is a recent extension. Here it uses a factor graph model for the specific estimation problem of equalization and use the sum-product algorithm to obtain the desired estimate. The reduced complexity message passing update equations are derived and detail the complexity of the resulting algorithms.
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通过因子图实现线性均衡
本文将因子图框架应用于线性均衡和决策反馈均衡技术,得到了一类新的低复杂度均衡算法。高斯过程的估计在以前的工作中已经得到了研究,而因子图在这个问题中的应用是最近的一个推广。这里使用因子图模型来解决均衡化的具体估计问题,并使用和积算法来获得期望的估计。推导了降低复杂度的消息传递更新方程,并详细说明了所得到的算法的复杂度。
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