Reputation-based hierarchically cooperative spectrum sensing scheme in cognitive radio networks

摘要

Cooperative spectrum sensing in cognitive radio is investigated to improve the detection performance of Primary User (PU). Meanwhile, cluster-based hierarchical cooperation is introduced for reducing the overhead as well as maintaining a certain level of sensing performance. However, in existing hierarchically cooperative spectrum sensing algorithms, the robustness problem of the system is seldom considered. In this paper, we propose a reputation-based hierarchically cooperative spectrum sensing scheme in Cognitive Radio Networks (CRNs). Before spectrum sensing, clusters are grouped based on the location correlation coefficients of Secondary Users (SUs). In the proposed scheme, there are two levels of cooperation, the first one is performed within a cluster and the second one is carried out among clusters. With the reputation mechanism and modified MAJORITY rule in the second level cooperation, the proposed scheme can not only relieve the influence of the shadowing, but also eliminate the impact of the PU emulation attack on a relatively large scale. Simulation results show that, in the scenarios with deep-shadowing or multiple attacked SUs, our proposed scheme achieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.