Equilibrium strategies in a channel sensing game in cognitive radio networks

We consider a channel sensing game in a cognitive radio network, where secondary users aim on maximizing their own utility by deciding on which channel to sense. We propose an algorithm for deriving Nash equilibrium strategies, and analyze the worst-case complexity of the algorithm. Finally, we examine differences between multiple possible equilibria in terms of total system utility and fairness.