Clustered hybrid energy-aware cooperative spectrum sensing (CHESS)

This work proposes a novel algorithm for energy-efficient and reliable spectrum sensing in a cognitive network. The algorithm relies on cooperation between secondary devices, that organize themselves in clusters defined according to both sensing reliability and energy efficiency. The proposed algorithm is compared by means of computer simulations with a simpler, non cluster-based cooperative sensing scheme. Simulation results highlight that the adoption of an energy-efficient, sensing-aware clustering algorithm in the sensing procedure can significantly improve both sensing reliability and network lifetime in secondary cognitive networks.