Robust route and channel selection in cognitive radio networks

In this paper, the joint route and channel selection problem with reliability guarantee in cognitive radio network (CRN) is addressed. Since the interference to licensed spectrum owners needs to be strictly controlled, cognitive radio enabled users (CUs) should vacate the using channel immediately on detecting licensed users and the end to end performance may be seriously degraded. Furthermore, the route constructed for a session may impose great negative influence on other current or latish sessions in the network. To account for these challenges, the route reliability is formulated based on the link valid probability and a metric named interference impact is proposed to value the influence of a route to the adjacent links. With the objective of minimizing the interference impact while providing throughput and reliability guarantee, the joint route and channel selection problem is formulated and shown to be in the form of integer nonlinear programming (INLP). Based on the analysis of the problem-specific feature, an on-demand route discovery algorithm is proposed to find reliable candidate routes, and a heuristic cross-layer optimization algorithm is proposed to choose the near-optimal route. Simulation results demonstrate that the proposed algorithm can guarantee the current route requirement while improving whole network throughput.