The advantages of millimeter-wave and large antenna arrays technologies for accurate wireless localization received extensive attentions recently. However, how to further improve the accuracy of wireless localization, even in the case of obstructed line-of-sight, is largely undiscovered. In this paper, the reconfigurable intelligent surface (RIS) is introduced into the system to make the positioning more accurate. First, we establish the three-dimensional RIS-assisted wireless localization channel model. After that, we derive the Fisher information matrix and the Cramer-Rao lower bound for evaluating the estimation of absolute mobile station position. Finally, we propose an alternative optimization method and a gradient decent method to optimize the reflect beamforming, which aims to minimize the Cramer-Rao lower bound to obtain a more accurate estimation. Our results show that the proposed methods significantly improve the accuracy of positioning, and decimeter-level or even centimeter-level positioning can be achieved by utilizing the RIS with a large number of reflecting elements.

中文翻译：

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可重构智能表面辅助无线定位

毫米波和大天线阵列技术在精确无线定位方面的优势最近受到广泛关注。然而，如何进一步提高无线定位的准确性，即使在视线受阻的情况下，在很大程度上还没有被发现。本文在系统中引入了可重构智能面（RIS），使定位更加准确。首先，我们建立了三维RIS辅助无线定位信道模型。之后，我们推导出 Fisher 信息矩阵和 Cramer-Rao 下界，用于评估绝对移动站位置的估计。最后，我们提出了一种替代优化方法和梯度下降方法来优化反射波束形成，它旨在最小化 Cramer-Rao 下界以获得更准确的估计。结果表明，所提出的方法显着提高了定位精度，利用具有大量反射元件的RIS可以实现分米级甚至厘米级定位。