Hitchhiking in Cognitive Radio Networks: Spectrum Sensing Assisted By Cores and Clusters

Spectrum sensing is a key part of cognitive radio networks (CRNs). There have been many works done on improving the accuracy of spectrum sensing results. In this paper, we focus on the phase before spectrum sensing is performed, that is, how to select a channel for sensing. We make use of the fact that nodes located in close geographical locations share similar channel information or sensing results at a given time. Our model enables each node to hitchhike in its spectrum sensing phase, by using other nearby nodes’ recent sensing results. Then the total number of channels that a node needs to sense before finding an available one can be reduced. We propose two frameworks for assisting nodes in selecting channels for spectrum sensing. One is the core-only structure, and another is the mixed cluster-core structure. We present the construction of two structures and the distributed spectrum sensing schemes, respectively. Considering the unpredictable primary user (PU) activities and channel dynamics, we also propose an evolution scheme for each node to adjust their selections of cores, in order to gain the most help. We conduct extensive simulations to study the performance of our frameworks. Keywords—Spectrum sensing, cognitive radio networks, cores, clusters, assistance-based.