Research Article
Wireless Access Virtualisation: Physical versus Virtual Capacities
@INPROCEEDINGS{10.4108/icst.5gu.2014.258122, author={Luisa Caeiro and Filipe D. Cardoso and Luis M. Correia}, title={Wireless Access Virtualisation: Physical versus Virtual Capacities}, proceedings={1st International Conference on 5G for Ubiquitous Connectivity}, publisher={IEEE}, proceedings_a={5GU}, year={2014}, month={12}, keywords={future internet virtual networks heterogeneous networks radio resource management resource allocation}, doi={10.4108/icst.5gu.2014.258122} }
- Luisa Caeiro
Filipe D. Cardoso
Luis M. Correia
Year: 2014
Wireless Access Virtualisation: Physical versus Virtual Capacities
5GU
IEEE
DOI: 10.4108/icst.5gu.2014.258122
Abstract
This paper addresses the virtualisation of wireless access in order to provide the required capacity (data rate) to a set of Virtual Base Stations (VBSs). The approach is based on a Virtual Radio Resource Allocation algorithm, OnDemandVRRA, which manages the allocation of the physical radio resources to the VBSs, in order to follow the contract and maintaining isolation among the VBSs, according to the type of guarantees of the VBSs, the amount of contracted capacity, and the VBSs’ utilisation. Taking the variability of the wireless medium into account, the algorithm continuously influences RRM mechanisms, namely admission control and MAC scheduling, to be aware of the VBSs’ state relative to the service level agreement, in order to compensate for this variability. The algorithm has been tested to evaluate its behaviour, concerning the amount of virtual contracted capacity versus the physical one. From simulation results, it can be concluded that the total capacity contracted for guaranteed VBSs should be limited according to the average capacity provided by the physical set of serving base stations. As an example, although the guaranteed VBS contracted capacity is always achieved, for the case where the guaranteed VBS contracted capacity is about 85% of the average cluster capacity, the cluster serving data rate decreases about 20% relative to the maximum achieved for the Best Effort Overbooking use case.