Cooperative Q-learning for multiple secondary users in dynamic spectrum access

In this paper, we present and evaluate learning schemes that allow multiple secondary users to locate and use spectrum opportunities effectively, thus improving efficiency of dynamic spectrum access (DSA) systems. Using simulations, we show that the proposed schemes achieve good performances in terms of throughput and fairness, and does so by interacting with and learning from the environment only, without requiring prediction models of the environment's dynamics and behaviors.