Effect of social relations on cooperative sensing in cognitive radio networks

Abstract

Previous works in cognitive radio networks (CRNs) have shown that cooperation in sensing improves sensing reliability and in turn enhances the network throughput. Although this altruistic cooperative behavior is accepted as the default mode of operation, it may often be invalid under practical circumstances. In this thesis, we loosen this assumption and introduce a cooperative mode of operation conditioned on social relations between Cognitive Radios (CRs). Rather than taking CRs as wireless devices with no context, we associate each CR with its user that has some social relations, e.g. friendship, community, selfishness. Using these relations among CRs, we propose a social-aware cooperative sensing scheme (SAC) and analyze its effects on sensing performance. We examine that exploiting social metrics is highly beneficial for cooperative sensing in CRNs and a model with social relations embedded will fit better to the next decade’s networking paradigm. Furthermore, we show in this thesis that a social aware sensing scheme outperforms a randomly cooperating candidate selecting scheme in terms of opportunity discovery, cooperation message overhead, and avoidance of cooperation with malicious users under various simulation scenarios.