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Intelligent Trajectory Inference Through Cellular Signaling Data
IEEE Transactions on Cognitive Communications and Networking ( IF 8.6 ) Pub Date : 2020-06-01 , DOI: 10.1109/tccn.2019.2961660
Heng Qi , Yanming Shen , Baocai Yin

As cellular networks get widely deployed, mobiles generate enormous amount of signaling data during every call and session. These signaling data contains rich location information. If at the network side, we can accurately locate large amounts of users using the signaling data, this will present opportunities for many novel applications, e.g., assisting wireless operators to troubleshoot the network performance, and providing location assisted service. However, it is challenging to accurately locate a user using only the signaling data due to its relatively high noise. Most existing solutions are based on fingerprint approaches, which apply supervised learning and are costly to build the fingerprint map. In this paper, we propose LTETrack, a novel trajectory tracking system using LTE signaling data. LTETrack only uses data that is already available in current LTE system and does not require any special hardware/software. LTETrack first makes a key observation that the Timing Advance (TA) data is suitable for trajectory tracking. TA value corresponds to the length of time that a signal takes to reach the cell tower from a mobile phone, which is required in cellular communication standard. LTETrack incorporates novel filtering techniques to identify the most accurate TAs, and then runs a map-matching algorithm to locate a user. We have evaluated LTETrack using traces collected in our city covering more than 800km. The results show that LTETrack achieves a high trajectory matching accuracy in metropolitan area.

中文翻译:

通过蜂窝信号数据进行智能轨迹推断

随着蜂窝网络的广泛部署,移动设备在每次呼叫和会话期间都会生成大量的信令数据。这些信令数据包含丰富的位置信息。如果在网络侧,我们可以使用信令数据准确定位大量用户,这将为许多新的应用提供机会,例如,协助无线运营商对网络性能进行故障排除,以及提供位置辅助服务。然而,由于其相对较高的噪声,仅使用信令数据来准确定位用户是具有挑战性的。大多数现有解决方案都基于指纹方法,这些方法应用监督学习并且构建指纹图的成本很高。在本文中,我们提出了 LTETrack,这是一种使用 LTE 信令数据的新型轨迹跟踪系统。LTETrack 仅使用当前 LTE 系统中已有的数据,不需要任何特殊的硬件/软件。LTETrack 首先观察到定时提前 (TA) 数据适用于轨迹跟踪。TA 值对应于信号从移动电话到达基站所需的时间长度,这是蜂窝通信标准所要求的。LTETrack 结合了新颖的过滤技术来识别最准确的 TA,然后运行地图匹配算法来定位用户。我们使用在我们城市收集的超过 800 公里的轨迹对 LTETrack 进行了评估。结果表明,LTETrack在大都市区实现了较高的轨迹匹配精度。LTETrack 首先观察到定时提前 (TA) 数据适用于轨迹跟踪。TA 值对应于信号从移动电话到达基站所需的时间长度,这是蜂窝通信标准所要求的。LTETrack 结合了新颖的过滤技术来识别最准确的 TA,然后运行地图匹配算法来定位用户。我们使用在我们城市收集的超过 800 公里的轨迹对 LTETrack 进行了评估。结果表明,LTETrack在大都市区实现了较高的轨迹匹配精度。LTETrack 首先观察到定时提前 (TA) 数据适用于轨迹跟踪。TA 值对应于信号从移动电话到达基站所需的时间长度,这是蜂窝通信标准所要求的。LTETrack 结合了新颖的过滤技术来识别最准确的 TA,然后运行地图匹配算法来定位用户。我们使用在我们城市收集的超过 800 公里的轨迹对 LTETrack 进行了评估。结果表明,LTETrack在大都市区实现了较高的轨迹匹配精度。LTETrack 结合了新颖的过滤技术来识别最准确的 TA,然后运行地图匹配算法来定位用户。我们使用在我们城市收集的超过 800 公里的轨迹对 LTETrack 进行了评估。结果表明,LTETrack在大都市区实现了较高的轨迹匹配精度。LTETrack 结合了新颖的过滤技术来识别最准确的 TA,然后运行地图匹配算法来定位用户。我们使用在我们城市收集的超过 800 公里的轨迹对 LTETrack 进行了评估。结果表明,LTETrack在大都市区实现了较高的轨迹匹配精度。
更新日期:2020-06-01
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