Spectrum Sensing Based on Cyclic Autocorrelation for Cognitive Radio

Spectrum sensing is the very task upon which the entire operation of cognitive radio rests. This paper introduces a new spectrum sensing method for cognitive radio systems based on cyclic autocorrelation. This method takes advantage of the amplitude of the cyclic autocorrelation to differentiate the noise from the primary users and detect the presence of the primary users. The method realizes the weak-signal detection in the given spectrum. Comparing with spectrum correlation method, this method has more bigger amplitude. Theoretical analysis for the algorithms is discussed. Computer simulation results are presented to verify the method.