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The impact of impedance matching on channel estimation in compact MIMO receivers

机译：阻抗匹配对紧凑型MIMO接收机中信道估计的影响

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Accurate channel estimates are essential to realize the high capacity of multiple-input, multiple-output (MIMO) communication channels. In compact receivers, prior work has shown that mutual coupling among antennas can significantly degrade the performance of channel estimation algorithms. However, this work did not consider the impact of coupling on observation noise, or the possible benefits of antenna impedance matching, which can profoundly alter the characteristics of observation noise. In this paper, we revisit the channel estimation problem for compact MIMO receivers. We consider a MIMO front-end that consists of coupled antennas, impedance matching and amplifiers, and includes physical models of antenna and amplifier noise. Using this model, we derive the error covariance of mimimum-mean-squared-error (MMSE) channel estimation and explore how it varies with front-end impedance and noise characteristics. We show the MMSE error covariance is always minimized by one kind of impedance matching, called minimum-noise-factor (MNF) matching. We present numerical results that compare the estimation error achievable with optimal matching to conventional antenna self-matching. These results suggest that, when conventional self-matching is used, estimation error is highly sensitive to amplifier noise in the presence of strong coupling. However, optimal MNF matching completely eliminates this sensitivity and significantly outperforms self-matching when amplifier noise is not negligible.
机译：准确的信道估计对于实现多输入多输出（MIMO）通信信道的高容量至关重要。在紧凑型接收机中，先前的工作表明，天线之间的相互耦合会大大降低信道估计算法的性能。但是，这项工作没有考虑耦合对观察噪声的影响，也没有考虑天线阻抗匹配可能带来的好处，后者可能会深刻改变观察噪声的特性。在本文中，我们重新审视了紧凑型MIMO接收机的信道估计问题。我们考虑一个MIMO前端，它由耦合天线，阻抗匹配和放大器组成，并包括天线和放大器噪声的物理模型。使用此模型，我们得出最小均方误差（MMSE）信道估计的误差协方差，并探讨其如何随前端阻抗和噪声特性而变化。我们显示，MMSE误差协方差始终通过一种称为最小噪声因子（MNF）匹配的阻抗匹配来最小化。我们提出了数值结果，该结果将最佳匹配与常规天线自匹配可获得的估计误差进行了比较。这些结果表明，当使用常规自匹配时，在存在强耦合的情况下，估计误差对放大器噪声高度敏感。但是，最佳的MNF匹配完全消除了这种灵敏度，并且在放大器的噪声不可忽略时，其性能远远优于自匹配。

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