An Enhanced Energy Detector for WRAN Systems Using Maximum-to-Mean Power Ratio

Spectrum sensing is the key challenge in implementing cognitive radio system, which enables unlicensed users to identify “white holes” in the spectrum allocated to primary users and utilize them efficiently. Recent studies have proposed three major sensing methods for WRAN systems, including matched filter, energy and feature detector. However, there are some drawbacks along with them. In this paper, we propose an enhanced energy detector that extends the ability of conventional one, which can differentiate the primary users from each other as well as the noise with different maximum-to-mean power ratio. Furthermore, a novel structure of cognitive radio detector employing the proposed algorithm is also analyzed to implement spectrum sensing. The simulation result shows that our proposed scheme performs well in the individual sensing environment and can satisfy the requirement with high detection probability.