Multi-armed bandit based policies for cognitive radio's decision making issues

Abstract

We suggest in this paper that many problems related to Cognitive Radio's (CR) decision making inside CR equipments can be formalized as Multi-Armed Bandit problems and that solving such problems by using Upper Confidence Bound (UCB) algorithms can lead to high-performance CR devices. An application of these algorithms to an academic Cognitive Radio problem is reported.