@misc{10481/80898,
year = {2022},
url = {https://hdl.handle.net/10481/80898},
abstract = {Radio Access Network (RAN) slicing involves several challenges. In particular, the Mobile Network
Operator (MNO) must ensure —before deploying each slice—that corresponding requirements can be
met throughout its lifetime. For ultra-Reliable Low Latency Communication (uRLLC) slices, the MNO
must guarantee the packet transmission delay within a delay budget with a certain probability. Most
existing solutions focus on allocating dynamically radio resources to maximize the number of packets,
whose transmission delay is within the delay budget. However, these solutions do not ensure the violation
probability is below a target value in the long term. In this paper, we focus on slicing from a planning
perspective. Specifically, we propose a Stochastic Network Calculus (SNC)-based model, which given
the amount of radio resources allocated for a uRLLC slice, the target violation probability and the traffic
demand distribution, provides the delay bound for such conditions. Additionally, we propose heuristics
for planning uRLLC slices. Interestingly, such heuristics benefit from the proposed SNC-based model to
compute the amount of radio resources to be assigned to each slice while its delay bound, given a target violation probability, is within the delay budget. We validate the SNC-based model and demonstrate the
effectiveness of the heuristics.},
organization = {This work is partially supported by the H2020 research and innovation project 5G-CLARITY (Grant No. 871428); the Spanish
Ministry of Economy and Competitiveness, The European Regional Development Fund (Project PID2019-108713RB-C53); and
the Spanish Ministry of Education, Culture and Sport (FPU Grant 17/01844)},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
keywords = {B5G},
keywords = {RAN slicing},
keywords = {uRLLC services},
keywords = {Stochastic network calculus},
keywords = {Delay bound modeling},
title = {A Stochastic Network Calculus (SNC)-based model for planning B5G uRLLC RAN slices},
doi = {10.1109/TWC.2022.3203937},
author = {Adamuz Hinojosa, Óscar Ramón and Sciancalepore, Vincenzo and Ameigeiras Gutiérrez, Pablo José and López Soler, Juan Manuel and Costa Pérez, Xavier},
}