Cyclo-stationarity based windowing method for spectrum sensing in cognitive radio networks

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access approach. To identify the free spectrum is one of the most challenging issues in cognitive radio systems. Cyclo-stationary feature detection is a detection scheme that satisfies in the area of fast, accurate & well perform in the presence of noise. The proposed method investigates the cyclo-stationary feature detection under different window techniques. In this paper the results of different windowing techniques are implemented along with their contour plots and a comparative study based on the simulation results is also proposed successfully. This technique based on window functions will be helpful to detect the primary user under low SNR conditions.