Blind Maximum Likelihood Carrier Frequency Offset Estimation for OFDM With Multi-Antenna Receiver
Blind Maximum Likelihood Carrier Frequency Offset Estimation for OFDM With Multi-Antenna Receiver
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DOI：
10.1109/tsp.2013.2245327
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发表时间：
2013-05
影响因子：
5.4
通讯作者：
Weile Zhang;Qinye Yin
中科院分区：
文献类型：
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作者：
Weile Zhang;Qinye Yin
在本文中，基于最大似然（ML）准则，我们提出了一种用于多天线接收机正交频分复用（OFDM）的盲载波频率偏移（CFO）估计方法。我们发现这种情况下的盲 ML 解决方案与单天线接收器的情况有很大不同。与传统的类MUSIC CFO搜索算法相比，我们提出的方法不仅具有适用于满载系统的优点，而且在存在空子载波的情况下可以获得更好的性能。事实证明，所提出的方法也优于为多天线接收机设计的几种现有估计器。提供的理论性能分析和数值结果都表明该方法可以在高信噪比（SNR）区域下实现克拉梅尔-饶界（CRB）。
In this paper, based on the maximum likelihood (ML) criterion, we propose a blind carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM) with multi-antenna receiver. We find that the blind ML solution in this situation is quite different from the case of single antenna receiver. As compared to the conventional MUSIC-like CFO searching algorithm, our proposed method not only has the advantage of being applicable to fully loaded systems, but also can achieve much better performance in the presence of null subcarriers. It is demonstrated that the proposed method also outperforms several existing estimators designed for multi-antenna receivers. The theoretical performance analysis and numerical results are provided, both of which demonstrate that the proposed method can achieve the Cramér-Rao bound (CRB) under the high signal-to-noise ratio (SNR) region.