Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks

摘要

In this paper, we consider the joint opportunistic routing and channelassignment problem in multi-channel multi-radio (MCMR) cognitive radio networks(CRNs) for improving aggregate throughput of the secondary users. We firstpresent the nonlinear programming optimization model for this joint problem,taking into account the feature of CRNs-channel uncertainty. Then consideringthe queue state of a node, we propose a new scheme to select proper forwardingcandidates for opportunistic routing. Furthermore, a new algorithm forcalculating the forwarding probability of any packet at a node is proposed,which is used to calculate how many packets a forwarder should send, so thatthe duplicate transmission can be reduced compared with MAC-independentopportunistic routing & encoding (MORE) [11]. Our numerical results show thatthe proposed scheme performs significantly better that traditional routing andopportunistic routing in which channel assignment strategy is employed.