Towards Zero Touch Configuration of 5G Non-Public Networks for Time Sensitive Networking - Luque Schempp, Francisco; Panizo-Jaime, Laura; Gallardo-Melgarejo, María del Mar; Merino-Gómez, Pedro; Rivas, Francisco Javier (IEEE, 2022)
The need to increase mobility and to remove cables in industrial environments is pushing 5G as a valuable communication system to connect traditional deterministic Ethernet-based devices. One alternative is the adoption of Time Sensitive Networking (TSN) standards over 5G Non-Public Networks (5G NPN) deployed in the company premises. This scenario presents several challenges, being the configuration of the 5G part the most relevant to provide latency, reliability and throughput balance suitable to ensure that all the TSN traffic can be delivered in time. Our research work addresses this problem from the perspective of the learning automata. Our aim is to learn from the live network to build a smart controller that can dynamically predict and apply a suitable configuration of the 5G NPN that can satisfy the requirements of the current TSN traffic. The article presents the main ideas of this novel approach.
This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in F. Luque-Schempp, L. Panizo, M. -d. -M. Gallardo, P. Merino and J. Rivas, "Toward Zero Touch Configuration of 5G Non-Public Networks for Time Sensitive Networking," in IEEE Network, vol. 36, no. 2, pp. 50-56, March/April 2022, doi: 10.1109/MNET.006.2100442.mission improvements or corrections. The Version of Record of this contribution is published in
Keywords: Sistemas de comunicaciones inalámbricos; 5G mobile communication; Learning automata; Predictive models; TSN; ITIS-Informe-Técnico