This paper presents a controller for the problem of Network Selection in 5G Networks, based on Reinforcement Learning. The problem of Network Selection and Traffic Steering is modeled as a Markov Decision Process and a Q- Learning based control solution is designed to meet 5G requirements, such as Quality of Experience (QoE) maximization, Quality of Service (QoS) assurance and load balancing. Numerical simulations preliminarily validate the proposed approach on a simulated scenario considered in the European project H2020 5G-ALLSTAR.
2020, 2020 European Control Conference (ECC), Pages 595-601
Traffic Steering and Network Selection in 5G Networks based on Reinforcement Learning (04b Atto di convegno in volume)
Delli Priscoli Francesco, Giuseppi Alessandro, Liberati Francesco, Pietrabissa Antonio
Gruppo di ricerca: Networked Systems