An Economic Framework for Routing and Channel Allocation in Cognitive Wireless Mesh Networks

We consider wireless mesh networks with cognitive ability of the wireless routers' radios. The cognitive ability is a cost efficient manner to increase available bandwidth but requires an adaptive bandwidth management mechanism to deal with dynamics of primary users' activities. In this paper, we investigate the joint channel allocation and routing in cognitive wireless mesh networks including the channel reuse opportunities in order to improve the network performance. In particular we propose an economic framework for adaptation and control of the network resources with the goal of network profit maximization. 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. Simulation results illustrate the network profit maximization and effectiveness of the proposed channel allocation scheme that is integrated with a channel reuse algorithm.