Understanding the performance of flexible functional split in 5G vRAN controllers: A Markov Chain-based model
We study Flexible Functional Split functionality of 5G vRAN controllers in 5G networks. We propose an innovative model, based on a Markov Chain, which can be used to characterize their performance. We consider both infinite and finite-buffer controllers. In the former, frames would not be lost (prov...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/21163 |
| Acceso en línea: | http://hdl.handle.net/10902/21163 |
| Access Level: | acceso abierto |
| Palabra clave: | Flexible Functional Split vRAN Controller Markov Chain Quasi-Birth-Death process |
| Sumario: | We study Flexible Functional Split functionality of 5G vRAN controllers in 5G networks. We propose an innovative model, based on a Markov Chain, which can be used to characterize their performance. We consider both infinite and finite-buffer controllers. In the former, frames would not be lost (provided the system works in a stable regime), and we thus focus on the time frames stay at the controller. For the finite-buffer controller, there might be losses, and we analyze the trade-off between time at the controller (which might hinder the stringent delay requirements of 5G services), and loss probability. Matrix-geometric techniques are used to resolve the corresponding Quasi-Birth-Death process. The validity of the proposed model is assessed by means of an extensive experiment campaign carried out over an ad-hoc eventdriven simulator, which is also used to broaden the analysis, considering different service rate distributions, as well as the variability of the studied performance indicators. The results show that the proposed model can be effectively exploited to tackle the dimensioning of these systems, as it sheds light on how their configuration impacts the expected delay and loss rate. |
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