Spectrum Sensing Based on Signal Sample Autocorrelation in Rayleigh Fading Channel

Spectrum Sensing is the first challenge of Cognitive Radio. The signal detection of primary users (PU) is a basic premise of spectrum sensing. In this paper, we adopt a method based on the sample autocorrelation of received signal to detect the existence of primary users' signals. It is called Sample Autocorrelation Matrix (SAM) method. Simulation results by using the randomly the captured digital television (DTV) signals show that the method outperforms the traditional energy detection method in detection performance. Due to the PU signals can be detected without the knowledge of the noise power under Rayleigh Fading channel environment, SAM method is robust to the noise uncertainty and the fading channel.