Article ID Journal Published Year Pages File Type
4957548 Pervasive and Mobile Computing 2017 18 Pages PDF
Abstract
We address the problem of estimating the population density from mobile phone data. After critically examining the relevant network-based data sources (CDR, VLR and passive monitoring systems) a novel methodology is presented with two key novelties. First, it enables the fusion of cell-level and Location Area-level data from heterogeneous data sources. Second, it considers a novel tessellation scheme based on cell coverage maps, instead of cell tower locations. Furthermore, it allows to integrate data from different network operators onto a common reference grid. Within the proposed framework, a Maximum-Likelihood formulation for the population density estimation problem is developed and tested via simulations, showing a significant gain over existing Voronoi-based schemes.
Keywords
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
Authors
, , , ,