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Analysis of RAN slicing for cellular V2X and mobile broadband services based on reinforcement learning

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Albonda, Haider Daami Resin
Pérez Romero, JordiMés informacióMés informacióMés informació
Document typeArticle
Defense date2020-03
PublisherEuropean Alliance for Innovation n.o.
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
ProjectSOFTWARIZACION Y OPTIMIZACION AUTOMATICA DE REDES DE ACCESO RADIO 5G MULTI-TENANT (AEI-TEC2017-82651-R)
Abstract
Radio Access Network (RAN) slicing is one of the key enablers to provide the design flexibility and enable 5G system to support heterogeneous services over a common platform (i.e., by creating a customized slice for each service). In this regard, this paper provides an analysis of a Reinforcement Learning (RL)-based RAN slicing strategy for a heterogeneous network with two generic services of 5G, namely enhanced mobile broadband (eMBB) and vehicle-to-everything (V2X). In particular, this paper investigates the RAN slicing by evaluating the proposed scheme under different algorithm configurations (i.e., number of actions of RL) and parameters in order to analyze the performance in terms of metrics such as RL convergence time and to demonstrate the capability of the algorithm to perform an efficient allocation of resources among slices. In addition, this study compares the results obtained by the proposed solution to those obtained with a Proportional Scheme.
CitationAlbonda, H.; Perez-Romero, J. Analysis of RAN slicing for cellular V2X and mobile broadband services based on reinforcement learning. "EAI Endorsed Transactions on Wireless Spectrum", Març 2020, vol. 4, núm. 13, p. 1-11. 
URIhttp://hdl.handle.net/2117/329738
DOI10.4108/eai.13-7-2018.163841
ISSN2312-6620
Publisher versionhttps://eudl.eu/doi/10.4108/eai.13-7-2018.163841
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  • GRCM - Radio Communication Research Group - Articles de revista [143]
  • Doctorat en Teoria del Senyal i Comunicacions - Articles de revista [161]
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