Exploiting primary user social features for reliability-driven routing in multi-hop cognitive radio networks

In this paper, we study the routing problem in multi-hop cognitive radio networks (CRNs). We observe that Primary Users (PUs) in CRNs exhibit unevenly geographic distribution due to their social behaviors. In the area with densely-distributed PUs, the low spectrum availability will severely decrease the Secondary Users (SUs) communication reliability. We are motivated to exploit Primary User (PU) social features to set up a multi-hop routing path providing reliable end-to-end communications. There are two main challenges: 1) how to quantitatively represent and characterize PU social features in CRNs; 2) given the knowledge of the PU social features, how to design an efficient route to improve the packet-forwarding reliability. We first propose the concept of PU community in CRNs. Maximum likelihood estimation method is then employed to predict the number of potential PUs. The estimated results effectively reflect the spectrum utilization, and hence, provide important information for PU community formulation. After that, considering the existence of PU community, we propose a hybrid routing scheme to alleviate the impact of PU community on packet-forwarding reliability. Simulation results demonstrate that the proposed scheme significantly improves the reliability of end-to-end communications.