Fusion Rule Based on Dynamic Grouping for Cooperative Spectrum Sensing in Cognitive Radio

Abstract

In this paper, we study the distributed cooperative spectrum sensing in heterogeneous cognitive radio networks, where each secondary user (SU) adopts a different spectrum sensing algorithm and experience a different channel environment. To solve the spectrum sensing problem, we propose a fusion rule based on dynamic grouping, which can be used in the mobility of the primary user and SUs. By introducing a grouping parameter, the proposed algorithm can realize the dynamic grouping of SUs. The SUs in group-1 will not be able to participate in the cooperation, and the SUs in groups-2 and groups-3 have different weighting factors. The proposed fusion rule is only required to process the independent decision result of each SU, which significantly reduces the data transmission overhead and processing delay. The simulation results show that the proposed fusion rule can effectively improve the dynamic grouping of SUs and fuse detection information, and outperform the OR rule, AND rule, equal gain combining, and maximum signal-to-noise ratio under the same conditions.