On Learning Mobility Patterns in Cellular Networks - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2016

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.
Fichier principal
Vignette du fichier
430537_1_En_61_Chapter.pdf (1.3 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01557594 , version 1 (06-07-2017)

Licence

Attribution

Identifiers

Cite

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⟩
55 View
91 Download

Altmetric

Share

Gmail Facebook X LinkedIn More