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A Distributed Q-Learning Approach for Adaptive Sleep Modes in 5G Networks

Ali El Amine 1, 2 Mauricio Iturralde 3 Hussein Al Haj Hassan 4 Loutfi Nuaymi 1, 2
1 IMT Atlantique - SRCD - Département Systèmes Réseaux, Cybersécurité et Droit du numérique
2 ADOPNET - Advanced technologies for operated networks
UR1 - Université de Rennes 1, IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire, IRISA-D2 - RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES
3 IRIT-RMESS - Réseaux, Mobiles, Embarqués, Sans fil, Satellites
IRIT - Institut de recherche en informatique de Toulouse
4 Université Libanaise
Keywords : Q-learning sleep modes 5G Energy consumption
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https://hal-imt-atlantique.archives-ouvertes.fr/hal-01988226
Contributor : Ali El Amine <>
Submitted on : Monday, January 21, 2019 - 4:02:53 PM
Last modification on : Wednesday, August 5, 2020 - 3:43:27 AM

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IMT-ATLANTIQUE | CNRS | UNIV-RENNES1 | SMS | UNIV-TLSE2 | CENTRALESUPELEC | IRISA | INRIA | UNIV-RENNES | UR1-UFR-ISTIC | UNIV-TLSE3 | UT1-CAPITOLE | INSTITUT-TELECOM | IRIT | IRIT-RMESS | INSA-RENNES

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Ali El Amine, Mauricio Iturralde, Hussein Al Haj Hassan, Loutfi Nuaymi. A Distributed Q-Learning Approach for Adaptive Sleep Modes in 5G Networks. WCNC 2019 : IEEE Wireless Communications and Networking Conference, Apr 2019, Marrakech, Morocco. ⟨10.1109/WCNC.2019.8885818⟩. ⟨hal-01988226⟩

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