Potential-Game-Based 5G RAN Slice Planning for GBR Services
Metadatos
Mostrar el registro completo del ítemAutor
Adamuz Hinojosa, Óscar Ramón; Muñoz Luengo, Pablo; Ameigeiras Gutiérrez, Pablo José; López Soler, Juan ManuelEditorial
IEEE
Materia
Blocking probability Game theory GBR services Radio resource allocation RAN slicing planning
Fecha
2023-01-11Referencia bibliográfica
Adamuz-Hinojosa, O... [et al.] (2023). Potential-Game-Based 5G RAN Slice Planning for GBR Services. IEEE Access. [10.1109/ACCESS.2023.3236103]
Patrocinador
H2020 Research and Innovation Project Beyond 5G Multi-Tenant Private Networks Integrating Cellular, Wi-Fi, and LiFi; Artificial Intelligence and Intent Based Policy (5G-CLARITY) 871428; Spanish Government; European Commission PID2019-108713RB-C53; Spanish Ministry of Economic Affairs and Digital Transformation TSI-063000-2021-28Resumen
The Radio Access Network (RAN) slice planning is a key phase within the RAN slice
management and orchestration process. Based on the performance requirements of requested RAN slices and
key performance indicators of the RAN and existing RAN slices, the RAN slice planning mainly consists of
deciding (a) the feasibility of deploying new RAN slices; (b) re-configuring the existing RAN accordingly;
and (c) the need to renegotiate the Service Level Agreements (SLAs) and/or expand the RAN (i.e., radio
resources, carriers, cells etc) if one or more RAN slices cannot be accommodated in a first attempt. Under
this context, we propose a framework for planning RAN slices which require their data sessions get a
Guaranteed Bit Rate (GBR) and the probability of blocking such sessions is below a threshold. To meet such
requirements, our framework plans the amount of prioritized radio resources for new and already deployed
RAN slices. We formulate the RAN slice planning as multiple ordinal potential games and demonstrate the
existence of a Nash Equilibrium solution which minimizes the average probability of blocking data sessions
for all the RAN slices. We perform detailed simulations to demonstrate the effectiveness of the proposed
solution in terms of performance, and renegotiation capability.