Exploring the Potential of Big Data Based Mobility Management
| Main Authors: | Ali, Zoraze, Baldo, Nicola, Mangues-Bafalluy, Josep, Giupponi, Lorenza |
|---|---|
| Format: | Proceeding |
| Terbitan: |
, 2015
|
| Online Access: |
https://zenodo.org/record/399235 |
Daftar Isi:
- In this paper, we explore the potential of applying a Big Data and machine learning approach to the LTE mobility management solutions. To this aim, we evaluate the performance of state-of-the-art handover algorithm, in presence of a coverage hole. The preliminary results show that, in this scenario the a state-of-the-art handover algorithm is unable to select the appropriate target cell for handover. This causes severe degradation in UE's Quality of experience (i.e., File Download Time). Hence we conclude that there is a signi cant room for improvement by designing novel mobility management solutions that exploit the information already available in the network through Big Data approaches.