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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Communication dans un congrès
Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.686-696, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_61〉
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Juan Sánchez-González, Jordi Perez-Romero, Ramon Agustí, Oriol Sallent. On Learning Mobility Patterns in Cellular Networks. Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.686-696, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_61〉. 〈hal-01557594〉

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