Optimization of multi-level hierarchical cluster-based spectrum sensing structure in cognitive radio networks

A compromise between sensing performance and overhead in cluster-based spectrum sensing for cognitive radio networks, is still a critical issue. This matter has attracted the attention of many researchers to tackle the trade-off between the performance and overhead. This paper proposes an energy efficient multi-level hierarchical structure algorithm using double fusion stages to minimize control overhead for a cluster with large number of sensors. An iterative algorithm is proposed to determine a suboptimal number of hierarchical levels. Optimal threshold, optimal fusion rule parameters and energy efficiency analysis are considered. The simulation results show that the proposed algorithm provides better detection performance, increases the throughput, and reduces considerably both the overhead and the reporting energy.