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)


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.


Clustering Cellular networks Mobility patterns 



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).


  1. 1.
    METIS 2020 Project:
  2. 2.
    El Hattachi, R., Erfanian, J. (eds.): NGMN 5G White Paper, NGMN Alliance, February 2015Google Scholar
  3. 3.
    Ramiro, J., Hamied, K.: Self-organizing Networks: Self-planning, Self-optimization and Self-healing for GSM, UMTS and LTE. Wiley, Chichester (2012)Google Scholar
  4. 4.
    I, C.-L., Liu, Y., Han, S., Wang, S., Liu, G.: On big data analytics for greener and softer RAN. IEEE Access, August 2015 Google Scholar
  5. 5.
    Imran, A., Zoha, A., Abu-Dayya, A.: Challenges in 5G: how to empower SON with Big Data for enabling 5G. IEEE Netw. 28, 27–33 (2014)CrossRefGoogle Scholar
  6. 6.
    Pérez-Romero, J., Sallent, O., Ferrús, R., Agustí, R.: Artificial intelligence-based 5G network capacity planning and operation. In: ISWCS Conference (2015)Google Scholar
  7. 7.
    Schreck, T. et al.: Visual cluster analysis of trajectory data with interactive Kohonen maps. In: IEEE Symposium on Visual Analysis Science and Technology, Columbus, USA, October 2008Google Scholar
  8. 8.
    Lee, J.-G., Han, J., Whang, K.-Y.: Trajectory clustering: a partition-and-group framework. In: SIGMOD, China (2007)Google Scholar
  9. 9.
    Andrienko, G., et al.: Interactive visual clustering of large collections of trajectories. In: IEEE Symposium on Visual Analysis Science and Technology, Atlantic City, USA, October 2009Google Scholar
  10. 10.
    Masciari, E.: A complete framework for clustering trajectories. In: 21st IEEE International Conference on Tools with Artificial Intelligence (2009)Google Scholar
  11. 11.
    Lee, H.J., et al.: Data stashing: energy-efficient information delivery to mobile sinks through trajectory prediction. In: ACM/IEEE IPSN Conference (2010)Google Scholar
  12. 12.
    Sas, B., Spaey, K., Blondia, C.: Classifying users based on their mobility behavior in LTE networks. In: 10th International Conference on Wireless and Mobile Communications (ICWMC) (2014)Google Scholar
  13. 13.
    Sas, B., Spaey, K., Blondia, C.: A SON function for steering users in multi-layer LTE networks based on their mobility behavior. In: VTC Spring Conference (2015)Google Scholar
  14. 14.
    3GPP TS 36.331 v12.7.0: Radio Resource Control (RRC); Protocol Specification (Release 12), September 2015 Google Scholar
  15. 15.
    Hapsari, W.A., Umesh, A., Iwamura, M., Tomala, M., Gyula, B., Sébire, B.: Minimization of drive tests solution in 3GPP. IEEE Commun. Mag. 50, 28–36 (2012)CrossRefGoogle Scholar
  16. 16.
    Han, J., Kamber, M.: Data Mining Concepts and Techniques, 2nd edn. Elsevier, Amsterdam (2006)zbMATHGoogle Scholar
  17. 17.
    Kohonen, T.: Essentials of the self-organizing map. Neural Netw. 37, 52–65 (2013)CrossRefGoogle Scholar
  18. 18.
    RapidMiner Studio:
  19. 19.
    Davies, D.L., Bouldin, D.W.: A cluster separation measure. IEEE Trans. Pattern Anal. Mach. Intell. PAM-1(2), 224–227 (1979). doi: 10.1109/TPAMI.1979.4766909 CrossRefGoogle Scholar

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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