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A novel structured channel estimation method for sparse channels with applications to multi-antenna digital TV receivers

机译:一种新型结构化信道估计方法,用于多天线数字电视接收器的应用稀疏通道

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In this paper we introduce a novel channel impulse response (CIR) estimation method, for sparse multipath channels, with applications to digital TV receivers with multiple antennae. Our new method uses symbol rate samples of the receiver matched filter output, and it is based on blending the least squares based channel estimation and the correlation based channel estimation methods. We first overview the shortcomings of the least squares and the correlation based channel estimation algorithm, where a training sequence is utilized in both cases. The performance of the new channel estimation method will be demonstrated, such that the channel estimation will be more robust, and the overall quality of the estimate will be improved by recovering the pulse shape which is naturally embedded in the overall channel impulse response. We will demonstrate how both methods can be combined effectively to minimize the problems associated with the effective channel delay spread being longer than the known training sequence can support. Examples are drawn from the ATSC digital TV 8-VSB system [1] with a multi-antenna receiver. 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. Finally we derive the noise variance estimator.
机译:在本文中,我们介绍了一种新的通道脉冲响应(CIR)估计方法,用于稀疏多径信道,其应用于具有多个天线的数字电视接收器。我们的新方法使用接收器匹配的滤波器输出的符号速率样本,并且基于混合基于基于方块的信道估计和基于相关的信道估计方法。我们首先概述最小二乘和基于相关的信道估计算法的缺点,其中在两种情况下使用训练序列。将说明新信道估计方法的性能,使得信道估计将更加稳健,并且通过恢复自然嵌入在整体通道脉冲响应中的脉冲形状,将改善估计的整体质量。我们将展示两种方法如何有效地组合,以最小化与有效信道延迟扩展相关的问题,这些问题比已知的训练序列能够支持。用多天线接收器从ATSC数字TV 8-VSB系统[1]中汲取示例。数字电视系统的延迟传播可以是符号持续时间的数百倍;然而,数字电视频道通常是稀疏,其中只有一些主要的多路径。最后,我们得出了噪声方差估计器。

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