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Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of...
In this paper, we analyze data from a large mobile phone provider in Europe, pertaining to time series of aggregate communication volume Ai,j(t) > 0 between cells i and j, for all pairs of cells in a city over a month. We develop a methodology for predicting the future (in particular whether two cells will talk to each other Ai,j(t) > 0) based on past activity. Our data set is sparse, with 80%...
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