Structured channel estimation based decision feedback equalizers for sparse multipath channels with applications to digital TV receivers

S. Ozen, W. Hillery, M. Zoltowski, S.M. Nereyanuru, M. Fimoff
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引用次数: 15

Abstract

In this paper, we investigate the performance of channel estimation based equalizers. We introduce two different channel estimation algorithms. Our first channel estimation scheme is a novel structured channel impulse response (CIR) estimation method for sparse multipath channels. The novel CIR estimation method was called blended least squares (BLS) which uses symbol rate sampled signals, based on blending the least squares based channel estimation and the correlation and thresholding based channel estimation methods. The second CIR estimation is called Variable thresholding (VT), and is based on improving the output of the correlation and thresholding based channel estimation method. We then use these two CIR estimates to calculate the decision feedback equalizer (DFE) tap weights. Simulation examples are drawn from the ATSC digital TV 8-VSB system. The delay spread for digital TV systems can be as long as several hundred times the symbol duration; however, digital TV channels are, in general, sparse where there are only a few dominant multipaths.
基于结构化信道估计的稀疏多径信道决策反馈均衡器及其在数字电视接收机中的应用
本文研究了基于信道估计的均衡器的性能。我们介绍了两种不同的信道估计算法。第一个信道估计方案是一种针对稀疏多径信道的结构化信道脉冲响应估计方法。将基于最小二乘的信道估计方法与基于相关和阈值的信道估计方法相混合,提出了一种基于码元率采样信号的混合最小二乘信道估计方法。第二种CIR估计称为可变阈值(VT),它是基于改进输出的基于相关和阈值的信道估计方法。然后,我们使用这两个CIR估计来计算决策反馈均衡器(DFE)分接权重。以ATSC数字电视8-VSB系统为例进行了仿真。数字电视系统的延迟扩展可达符号持续时间的数百倍;然而,数字电视频道通常是稀疏的,只有少数几个占主导地位的多路径。
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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