Correlation-based spectrum sensing in cognitive radio
Wenfang Xia, Shu Wang, Wei Liu, Wenqing Cheng · 2009
Spectrum sensing is an essential function for cognitive radio systems. Based on the observation that signal samples usually are correlated due to various reasons, such as oversampling, multipath propagation and correlation among raw signals, a correlation-based detection method is proposed to differentiate signals from noise in this paper. Sensing performance of the proposed method is analyzed theoretically when primary signals are fully correlated. Its complexity is compared with that of energy detection and threshold setting is discussed under an estimated false alarm probability. However, the algorithm is inferior to energy detection in sensing performance when signal samples are uncorrelated. To overcome this disadvantage, an adaptive detection model is developed. Simulations based on captured ATSC DTV signals and analog PAL TV signals are presented to verify the performance of the proposed method.