An Improved Spectrum Sensing Method: Energy-Autocorrelation-Based Detection Technology

Due to the environmental noise, variance is uncertain and unknown. The energy-based detection (ED) technology has many shortcomings in cognitive radio. In the paper, an energy-autocorrelation detection (EAD) algorithm is proposed to overcome these challenges, taking advantage of the different characteristics of Gauss white noise and signal. Two statistics are structured based on energy and autocorrelation of samples. This spectrum sensing algorithm can lead to stable and accurate detection performance without any prior information on noise and signal. It is testified in the simulation that the energy-autocorrelation-based detection is much better than energy-based detection; moreover, the impact of some parameters of the algorithm is also simulated and discussed.