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An Improved Subspace-Based Algorithm for Blind Channel Identification Using Few Received Blocks

机译：一种改进的基于子空间的接收块少的盲信道识别算法

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摘要

In the last decade, several subspace-based algorithms for blind channel identification in zero-padded systems were introduced. These subspace-based methods are attractive because highly accurate estimates of the channel can be obtained by using only a few received blocks. However, they do not work when applied to the zero-padded orthogonal frequency division multiplexing systems (ZP-OFDM) with virtual carriers. In this paper, we propose two improvements on an earlier subspace-based blind channel estimation method for such systems. Firstly, we introduce a simple noise weighting approach. Unlike most of the earlier methods, the proposed weighting matrix is diagonal and it is independent of the channel noise variance and SNR. By doing so, the performance of previous work is significantly enhanced. Secondly, we extend the blind estimation method to ZP-OFDM systems with virtual carriers. Simulations are carried out to demonstrate the merits of the proposed method.
机译：在过去的十年中，引入了几种基于子空间的零填充系统中盲信道识别算法。这些基于子空间的方法之所以具有吸引力，是因为仅使用几个接收到的块就可以获得高度准确的信道估计。但是，当将其应用于具有虚拟载波的零填充正交频分复用系统（ZP-OFDM）时，它们将不起作用。在本文中，我们提出了针对此类系统的基于子空间的早期盲信道估计方法的两项改进。首先，我们介绍一种简单的噪声加权方法。与大多数早期方法不同，建议的加权矩阵是对角线的，并且独立于信道噪声方差和SNR。这样，可以显着提高先前工作的性能。其次，我们将盲估计方法扩展到具有虚拟载波的ZP-OFDM系统。仿真表明了该方法的优点。

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