A framework for routing and channel allocation in cognitive wireless mesh networks

We consider wireless mesh networks where some of the wireless routers also play a role of gateways to the internet. The assumed cognitive ability of the routers´ radios is a cost efficient manner to increase available bandwidth but requires an adaptive bandwidth management mechanism to deal with dynamics of primary users´ activities. To cope with this issue we propose an economic framework for adaptation and control of the network resources with the final goal of the network profit maximization. The main issues considered are channel allocation and call admission and routing. The economic framework is based on the notion of state dependent node shadow price that is derived from Markov decision theory. The node shadow prices are used as routing metrics while their average values are used to allocate the channels among the different nodes. The simulation results demonstrate the performance of the proposed methodology.