Reinforcement learning demonstrator for opportunistic spectrum access on real radio signals
Résumé
This demonstration presents a proof-of-concept for opportunistic spectrum access. It particularly focuses on reinforcement learning algorithm called UCB (Upper Confidence Bound) designed by the machine learning community to solve the MAB problem (Multi-Armed Bandit). The demonstrator shows the first worldwide implementation of reinforcement learning algorithms for OSA (opportunistic spectrum access) on real radio environment using USRP N210 platforms.
Domaines
Electronique| Origine | Fichiers éditeurs autorisés sur une archive ouverte |
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