Combined channel assignment and network coded opportunistic routing in cognitive radio networks

In this paper, we investigate the joint opportunistic routing and channel assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks (CRNs) for improving the aggregate throughput of the secondary users. We first present the nonlinear programming optimization model for this joint problem, taking into account the feature of CRNs-channel uncertainty. In order to reduce the computational complexity of the problem, we present a heuristic algorithm to select forwarding candidates and assign channels in CRNs, including candidate selection algorithm considering the queue state of a node and expected transmission count (ETX), and channel assignment algorithm taking into account the transmission time and the available time of a given channel. Our simulation results show that the proposed scheme Channel Assignment and Network Coded Opportunistic Routing, (CANCOR) performs better than the traditional routing and classical opportunistic routing in which channel assignment strategy is employed.