Low complexity energy-efficient multilevel cluster-based cooperative spectrum sensing in cognitive radio networks

The multi-level hierarchical cluster based spectrum sensing (MH-CBSS) algorithm balances between the detection performances and the incurred overhead. However, the MH-CBSS algorithm requires computational burden. In this work, we propose a modified MH-CBSS algorithm that reduces the computational requirements by initially defining the number of reporting cognitive radios (CRs). Simulation results show that the detection performance of the modified algorithm outperforms the MH-CBSS algorithm over Rayleigh and Nakagami fading channels.