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Multilayered reinforcement learning approach for radio resource management
Kevin, Collados; Gorricho Moreno, Juan Luis; Serrat Fernández, Juan; Hu, Zheng
Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica; Universitat Politècnica de Catalunya. MAPS - Gestió, Polítiques de Preus i Serveis en Xarxes de Nova Generació
In this paper we face the challenge of designing self-tuning systems governing the working parameters of base stations on a mobile network system to optimize the quality of service and the economic benefit of the operator. In order to accomplish this double objective, we propose the combined use of fuzzy logic and reinforcement learning to implement a self-tuning system using a novel approach based on a two-agent system. Different combinations of reinforcement learning techniques, on both agents, have been tested to deduce the optimal approach. The best results have been obtained applying the Q-learning technique on both agents, clearly outperforming the alternative of using non-learning algorithms.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Comunicacions mòbils
Àrees temàtiques de la UPC::Matemàtiques i estadística::Lògica matemàtica
Fuzzy logic
Mobile communication systems
Computer networks
Fuzzy logic
Learning algorithms
Quality of service
Lògica difusa
Comunicacions mòbils, Sistemes de
Attribution-NonCommercial-NoDerivs 3.0 Spain

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