Published in

2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2020

DOI: 10.1109/wcncw48565.2020.9124723



Export citation

Search in Google Scholar

Network Selection in 5G Networks Based on Markov Games and Friend-or-Foe Reinforcement Learning

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO


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.