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On Learning Mobility Patterns in Cellular Networks

Abstract : This paper considers the use of clustering techniques to learn the mobility patterns existing in a cellular network. These patterns are materialized in a database of prototype trajectories obtained after having observed multiple trajectories of mobile users. Both K-means and Self-Organizing Maps (SOM) techniques are assessed. Different applicability areas in the context of Self-Organizing Networks (SON) for 5G are discussed and, in particular, a methodology is proposed for predicting the trajectory of a mobile user.
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Submitted on : Thursday, July 6, 2017 - 1:55:00 PM
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Juan Sánchez-González, Jordi Perez-Romero, Ramon Agustí, Oriol Sallent. On Learning Mobility Patterns in Cellular Networks. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.686-696, ⟨10.1007/978-3-319-44944-9_61⟩. ⟨hal-01557594⟩



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