This paper presents a control solution for the optimal network selection problem in 5G heterogeneous networks. The control logic proposed is based on multi-agent Friend-or-Foe Q-Learning, allowing the design of a distributed control architecture that sees the various access points compete for the allocation of the connection requests. Numerical simulations validate conceptually the approach, developed in the scope of the EU-Korea project 5G-ALLSTAR
Dettaglio pubblicazione
2020, 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Pages 1-5
Network Selection in 5G Networks Based on Markov Games and Friend-or-Foe Reinforcement Learning (04b Atto di convegno in volume)
Giuseppi Alessandro, De Santis Emanuele, Delli Priscoli Francesco, Won Seok Ho, Choi Taesang, Pietrabissa Antonio
ISBN: 978-1-7281-5178-6
Gruppo di ricerca: Networked Systems
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