Lattice based soft-constraint satisfaction multi-modulus blind equalization algorithm

S. Abrar
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引用次数: 1

Abstract

In this paper, a method of accelerating the speed of Convergence of a blind equalization algorithm is examined. It is shown that as in conventional equalizers the orthogonalizing properties of lattice algorithms make them appear attractive in blind equalization of a channel. The lattice is applied to a newly proposed blind equalization algorithm [I], [2], known as soft-constraint satisfaction multi-modulus algorithm (SCS-MM-I). Experiments show that the introduction of a stochastic gradient lattice structure in SCS-MM-I results in an increase of convergence rate by an order of magnitude.
基于点阵的软约束满足多模盲均衡算法
本文研究了一种提高盲均衡算法收敛速度的方法。与传统均衡器一样,点阵算法的正交化特性使其在信道盲均衡中显得很有吸引力。该格被应用于一种新提出的盲均衡算法[I],[2],称为软约束满足多模算法(SCS-MM-I)。实验表明,在SCS-MM-I中引入随机梯度晶格结构,使收敛速度提高了一个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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