Non-parametric Blind Spectrum Sensing Based on Censored Observations for Cognitive radio
In cognitive radio, spectrum sensing is a challenging task. In this paper, a spectrum sensing method based on censored observations is proposed. We call it as Censored Anderson Darling (CAD) sensing. We present the performance of the CAD sensing method with receiver operating characteristics (ROC) in fading channels using simulations. It is observed that the proposed method outperforms the conventional energy detection (ED) at lower signal to noise ratio. It also provides better detection performance compared to Ordered Statistics (OS) based sensing method. We also use the CAD sensing method assuming noise uncertainty. It means noise variance at secondary user(SU) is unknown. We call it as Blind CAD sensing (B-CAD). We also show that the B-CAD outperforms the energy detection.
spectrum sensing goodness of fit test quasi-static channel censored data