Accurate Localization Using LTE Signaling Data

Lei Ni, Yuxin Wang, Haoyang Tang, Zhao Yin, Yanming Shen
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引用次数: 20

Abstract

In this paper, we propose a novel localization algorithm using LTE signaling data. Specifically, we use TA (Timing Advance) and RSRP (Reference Signal Receiving Power) data that are required in LTE standard and already available in current LTE systems. The combination of (TA, RSRP) is used as a signature, and one can expect that different locations will have distinctive signatures. Our real world data first showed that both TA and RSRP at a particular location have a small variance, and therefor good for localization purpose. We then consider the spatial-temporal dependencies of these data to improve the localization accuracy. We design and implement a novel machine learning based algorithm to infer a user's latitude-longitude given a (TA, RSRP) measurement. We have evaluated our system using traces collected in our city covering more than 800 km. The results show that our cellular signaling based localization algorithm achieves a median localization accuracy around 25 m.
使用LTE信令数据进行精确定位
在本文中,我们提出了一种新的使用LTE信令数据的定位算法。具体来说,我们使用LTE标准中要求的TA(定时提前)和RSRP(参考信号接收功率)数据,这些数据已经在当前的LTE系统中可用。使用(TA, RSRP)的组合作为签名,可以预期不同的位置将具有不同的签名。我们的真实世界数据首先表明,特定位置的TA和RSRP都有很小的差异,因此有利于定位目的。然后,我们考虑这些数据的时空依赖关系,以提高定位精度。我们设计并实现了一种新的基于机器学习的算法来推断给定(TA, RSRP)测量的用户的经纬度。我们利用在我们城市中收集的800多公里的痕迹对我们的系统进行了评估。结果表明,基于蜂窝信号的定位算法实现了25 m左右的中值定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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