Citation:
Mancuso, V., Castagno, P., Sereno, M. y Marsan, M.A. (2020). Modeling MTC and HTC Radio Access in a Sliced 5G Base Station. IEEE Transactions on Network and Service Management.
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Comunidad de Madrid European Commission Ministerio de Economía y Competitividad (España)
Sponsor:
This work is partially supported by the Region of Madrid through the TAPIR-CM project (S2018/TCS-4496), by a Ramon y Cajal grant (ref: RYC-2014-16285) from the Spanish Ministry of Economy and Competitiveness, and by HOME (Hierarchical Open Manufacturing Europe) project supported by the Regione Piemonte, Italia (framework program PORFESR 14/20). This work was supported by the EU Commission through the 5GROWTH project (grant agreement no. 856709).
Project:
info:eu-repo/grantAgreement/EC/H2020/856709 Comunidad de Madrid. S2018/TCS-4496 Gobierno de España. RYC-2014-16285
Keywords:
Radio access network
,
5G
,
Base station
,
Slicing
,
Queuing networks
,
HTC and MTC coexistence
In this article, we develop a modeling framework to describe the uplink behavior of radio access in a sliced cell, including most features of the standard 3GPP multiple access procedures. Our model allows evaluating throughput and latency of each slice, as a fIn this article, we develop a modeling framework to describe the uplink behavior of radio access in a sliced cell, including most features of the standard 3GPP multiple access procedures. Our model allows evaluating throughput and latency of each slice, as a function of cell parameters, when resources are in part dedicated to individual slices and in part shared. The availability of an accurate model is extremely important for the automated run time management of the cell and for the correct setting of its parameters. Indeed, our model considers most details of the behavior of sliced 5G cells, including Access Class Barring (ACB) and Random Access CHannel (RACH) procedures, preamble decoding, Random Access Response (RAR), and Radio Resource Control (RRC) procedures. To cope with a number of slices devoted to serve various co-deployed tenants, we derive a multi-class queueing model of the network processor. We then present (i) an accurate and computationally efficient technique to derive the performance measures of interest using continuous-time Markov chains, which scales up to a few slices only, and (ii) tight performance bounds, which are useful to tackle the case of more than a fistful of slices. We prove the accuracy of the model by comparison against a detailed simulator. Eventually, with our performance evaluation study, we show that our model is very effective in providing insight and guidelines for allocation and management of resources in cells hosting slices for services with different characteristics and performance requirements, such as machine type communications and human type communications.[+][-]