Cyclostationary Feature Detection for Spectrum Sensing in Cognitive Radio Network

This paper focus on cyclostationary feature detection based spectrum sensing for accurate, fast and efficient primary signal detection. When secondary users fail to realize the white space, either it will cause a serious interference with primary user or a failure to reuse the unoccupied band. There is wide variety of schemes possible to detect the vacant band and the basic among them is the energy detection but is not efficient. Cyclostationary feature detection (CFD) based spectrum sensing exploit the second order periodicity of modulated signal .Cyclostationary based detection gives excellent information of signal characteristics even at very low SNR due to its robustness to the noise also realizes the modulation scheme used for transmitting the signal. Spectrum sensing or presence of primary user (PU) is detection is done in LabVIEW environment in this work.