Stability-Capacity-Adaptive Routing for High-Mobility Multihop Cognitive Radio Networks

In high-mobility cognitive radio networks (CRNs), the fast topology changes increase the complexity of the routing scheme. In this paper, we propose a novel CRN routing scheme that considers the path stability and node capacity. First, a realistic mobility model is proposed to describe the movement of highly mobile airborne nodes [e.g., unmanned aerial vehicles (UAVs)] and estimate the link stability performance based on node movement patterns. Second, we propose a CRN topology management scheme based on a clustering model that considers radio link availability, and the cluster heads (CHs) are selected based on the node degree level, the average number of hops, and channel switching from member nodes to the CH. Third, we propose two new common control channel (CCC) selection schemes based on the node contraction concept and the discrete particle swarm optimization algorithm. The intercluster control channels and gateways are selected from the CHs, considering the average delay of control information transmission between two CHs, as well as the total throughput of control channels. Finally, a novel routing scheme is proposed that tightly integrates with the channel assignment scheme based on the node capacity. Our simulation results show that our proposed CCC selection scheme has high throughput and small transmission time. Compared with other popular CRN routing approaches, our proposed routing scheme achieves lower average end-to-end delay and higher packet delivery ratio for high-mobility CRN applications (such as airborne surveillance).