Routing in Reinforcement Learning Based Cognitive Radio Networks

Cognitive Radio (CR) technology is a promising technology that allows unlicensed users to access licensed spectrum bands opportunistically in a dynamic and noninterfering manner. Thus, using Cognitive Radio Networks (CRNs) spectrum efficiency can be increased by allowing the secondary users (SUs) to access the licensed band dynamically and opportunistically without interfering the primary users (PUs). Cognitive Radio Networks can be defined in the context of machine learning as the network which improves its performance through experience gained over a period of time without complete information about the environment in which it operates. Reinforcement learning is one such type of machine learning concerned with how software agents or learning agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Thus, the dynamism and opportunism can be learned by reinforcement learning (RL).