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On Learning Mobility Patterns in Cellular Networks

  • Juan Sánchez-GonzálezEmail author
  • Jordi Pérez-Romero
  • Ramon Agustí
  • Oriol Sallent
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 475)

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.

Keywords

Clustering Cellular networks Mobility patterns 

Notes

Acknowledgements

This work has been supported by the EU funded H2020 5G-PPP project SESAME under the grant agreement no 671596 and by the Spanish Research Council and FEDER funds under RAMSES grant (ref. TEC2013-41698-R).

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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Juan Sánchez-González
    • 1
    Email author
  • Jordi Pérez-Romero
    • 1
  • Ramon Agustí
    • 1
  • Oriol Sallent
    • 1
  1. 1.Universitat Politècnica de Catalunya (UPC)BarcelonaSpain

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