Research Article
Distributed Load Balancing for Future 5G Systems On-board High-Speed Trains
@INPROCEEDINGS{10.4108/icst.5gu.2014.258110, author={Leonardo Goratti and Stefano Savazzi and Ali Parichehreh and Umberto Spagnolini}, title={Distributed Load Balancing for Future 5G Systems On-board High-Speed Trains}, proceedings={1st International Conference on 5G for Ubiquitous Connectivity}, publisher={IEEE}, proceedings_a={5GU}, year={2014}, month={12}, keywords={5g distributed cooperative system high speed train load balancing}, doi={10.4108/icst.5gu.2014.258110} }
- Leonardo Goratti
Stefano Savazzi
Ali Parichehreh
Umberto Spagnolini
Year: 2014
Distributed Load Balancing for Future 5G Systems On-board High-Speed Trains
5GU
IEEE
DOI: 10.4108/icst.5gu.2014.258110
Abstract
The surge of mobile broadband Internet access has nowadays reached the critical point that traffic is projected to increase dramatically in the next years and even the 4G UMTS Long term Evolution (LTE) cellular technology and its advanced version LTE-A might lack enough flexibility and system reconfiguration capability. For these reasons, the quest for the Fifth Generation (5G) of cellular technology has started. In the context of users that require high Quality of Experience (QoE) anytime and anywhere, users on-board of fast moving vehicles such as high-speed trains represent an important market segment for both telecom operators and transportation companies. In particular, people who are moving for business everyday require low latency and high throughput Internet connectivity even when moving at hundreds of kilometers per hour. In this landscape, novel algorithms can find their space in future 5G systems to cope with fast resource (re)allocation in the presence of large Doppler spread and high handover frequency. Focusing on a high-speed train (HST), in this paper we propose a simple but effective distributed load balancing algorithm to relieve service interruption caused by frequent handovers in high mobility scenarios. Our results show the effectiveness of the solution while leveraging on the concept of cell edge intelligence.