Performance measurements-based estimation of radio resource requirements for slice admission control

The network slicing capability introduced in 5G systems facilitates the realisation of flexible multi-tenant networks. Network slicing enables the partition of a common shared network in several logical networks, each configured to fulfil specific service requirements. In scenarios where the lifecycle of network slices has to be managed dynamically (e.g. allocation, modification and deallocation of network slices in response to changing tenants’ needs), slice admission control becomes a central function to assure that the set of slices concurrently activated count with the sufficient resources to fulfil their service requirements. Slice admission control is particularly challenging for the Radio Access Network (RAN) part of a slice, because the amount of required radio resources is highly dependent on the characteristics of the deployment environment and type of cells. In this context, this paper presents a functional data-analytics framework along with a new analytical methodology for estimating the radio resource requirements for RAN slice admission control. Specifically, in order to characterise the propagation and interference conditions in each cell, the proposed resource estimation method leverages statistical information extracted via data analytics from the cell performance measurements collected at the management plane. Results show the benefits of the proposed estimation method under different types of cell deployments.This work has been supported by the EU funded H2020 5G-PPP project 5G ESSENCE under the grant agreement 761592, by the Spanish Research Council and FEDER funds under SONAR 5G grant (ref. TEC2017-82651-R) and by the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia under grant 2018FI_B_00412.Peer Reviewe