论文标题
贝叶斯在手机网络中的位置估计
Bayesian estimate of position in mobile phone network
论文作者
论文摘要
传统的移动电话定位方法基于以下假设:呼叫详细信息记录中记录的小区塔的地理位置(CDR)是设备位置的代理。然后,基于整个细胞塔网络构建了Voronoi Tessellation,该镶嵌物被视为坐标系,设备位于CDR中记录的细胞塔的Voronoi Polygon中。如果基于Voronoi的定位正确,则设备轨迹的独特性很高,并且可以基于其记录的位置的3-4识别设备。我们提出并研究了一种基于每个天线参数的知识和连接数量的概率方法,该方法取决于与天线的距离。基于Voronoi的基于Voronoi和现实世界的布局之间的关键区别在于天线服务区域的必不可少的重叠:位于电池塔的多边形中的设备可以由网络系统选择的更遥远的天线来服务,以平衡网络负载。这种重叠太显着而无法忽略。结合网络中每个天线可用连接数量的距离分布的数据,我们通过应用贝叶斯推断并构建设备位置的现实分布来解决重叠问题。概率设备定位需要对手机数据分析进行全面修订,我们以隐私风险估计为重点进行讨论。
The traditional approach to mobile phone positioning is based on the assumption that the geographical location of a cell tower recorded in a call details record (CDR) is a proxy for a device's location. A Voronoi tessellation is then constructed based on the entire network of cell towers and this tessellation is considered as a coordinate system, with the device located in a Voronoi polygon of a cell tower that is recorded in the CDR. If Voronoi-based positioning is correct, the uniqueness of the device trajectory is very high, and the device can be identified based on 3-4 of its recorded locations. We propose and investigate a probabilistic approach to device positioning that is based on knowledge of each antennas' parameters and number of connections, as dependent on the distance to the antenna. The critical difference between the Voronoi-based and the real world layout is in the essential overlap of the antennas' service areas: the device that is located in a cell tower's polygon can be served by a more distant antenna that is chosen by the network system to balance the network load. This overlap is too significant to be ignored. Combining data on the distance distribution of the number of connections available for each antenna in the network, we succeed in resolving the overlap problem by applying Bayesian inference and construct a realistic distribution of the device location. Probabilistic device positioning demands a full revision of mobile phone data analysis, which we discuss with a focus on privacy risk estimates.