An overview on non-parametric spectrum sensing in cognitive radio

The scarcity of frequency spectrum used for wireless communication systems has attracted a considerable amount of attention in recent years. The cognitive radio (CR) terminology has been widely accepted as a smart platform mainly aimed at the efficient interrogation and utilization of permitted spectrum. Non-parametric spectrum sensing, or estimation, represents one of the prominent tools that can be proposed when CR works under an undetermined environment. As such, the periodogram, filter bank, and multi-taper methods are well considered in many studies without relying on the transmission channel's characteristics. A unified approach to all these non-parametric spectrum sensing techniques is presented in this paper with analytical and performance comparison using simulation methods. Results show that the multi-taper method outperforms the others.