Policies for channel allocation in cognitive radio networks using game theory

Abstract

Cognitive radio networks evolve according to the actions of selfish users who act independently. The eventual state reached in most of the cases by such a system is a Nash Equilibrium (NE). Multiple NE with different qualities may exist. In this work we consider the problem of allocating channels to multiple transceivers. Based on policies derived from various network metrics we develop a way to initialize the allocation and choose the appropriate channel for each user to push the system towards a higher normalized cumulative total throughput of the CRN. A novel equation to allocate channels is also derived. The improvement is confirmed by our simulation results.