Two types of users, Primary Users (PUs) and Secondary Users (SUs), share common spectrum bands in Cognitive Radio Networks (CRNs). SUs communicate through un-assigned spectrum bands without disrupting PUs. It is widely assumed that the activities of PUs follow some probabilistic models regardless of time, geography and social relationships. However, the time-and-geography-dependent social activity patterns of PUs can definitely be taken advantage of by SUs to obtain more spectrum opportunities and help with featuring the fundamental characteristics of CRNs in a more meaningful way. Unfortunately, this fact has been overlooked. This project conducts a comprehensive study on designing routing protocols/algorithms integrating technologies from social networks and traditional CRNs. New statistic learning models and community detection methods considering PUs' activity patterns are proposed. The fundamental properties of secondary networks under certain activity patterns and community patterns of PUs are investigated. Corresponding guidance for designing upper layer protocols for CRNs is provided. This project has a strong impact on both theoretical and practical aspects of CRNs as well as social networks. Considering the characteristics of PUs, new research challenges and significance of the corresponding problems are elaborated. The project integrates research and education with the intent of attracting undergraduate and graduate students to the area of CRNs. It also outreaches high school students. The outcomes will provide valuable resources for the CRN society and will be published in conferences, journals, and on the Internet.
