| Title |
Using Smart City Data in 5G Self-Organizing Networks |
| ID_Doc |
38109 |
| Authors |
Cia, MD; Mason, F; Peron, D; Chiariotti, F; Polese, M; Mahmoodi, T; Zorzi, M; Zanella, A |
| Title |
Using Smart City Data in 5G Self-Organizing Networks |
| Year |
2018 |
| Published |
Ieee Internet Of Things Journal, 5, 2 |
| Abstract |
So far, research on Smart Cities and self-organizing networking techniques for fifth-generation (5G) cellular systems has been one-sided: a Smart City relies on 5G to support massive machine-to-machine (M2M) communications, but the actual network is unaware of the information flowing through it. However, a greater synergy between the two would make the relationship mutual, since the insights provided by the massive amount of data gathered by sensors can be exploited to improve the communication performance. In this paper, we concentrate on self-organization techniques to improve handover efficiency using vehicular traffic data gathered in London. Our algorithms exploit mobility patterns between cell coverage areas and road traffic congestion levels to optimize the handover bias in heterogeneous networks and dynamically manage mobility management entity (MME) loads to reduce handover completion times. |
| PDF |
https://kclpure.kcl.ac.uk/portal/files/79580877/SON_IoT_2017.pdf
|
