A Review on Cooperative Spectrum Sensing using Cyclostationary Feature Detection for Cognitive Radio Networks

With some recent developments in the field of wireless communication rapidly, users are getting a number of applications which require the precious bandwidth to work on. As the bandwidth is limited, the available spectrum is being congested day by day. Cognitive Radio System (CRS) plays an important role in such scenario. It adapts the parameters and protocols dynamically to provide unused spaces in the total usable spectra. There are a number of ways to detect the unused spectrum/holes/white spaces like Energy Detection, Matched Filter Detection, Cyclostationary Feature Detection (CFD), Wavelet Transform, Covariance based Method. Spectrum sensing can be significantly improved by allowing different users to share their local sensing observations and to cooperatively decide on the licensed spectrum occupancy. The main advantage of this technique is that it is robust to random noise and interference from other modulated signals, no synchronization is required and it gives optimal detection performance in very low SNR region. On the other hand, it has some limitations such as high computational complexity and increased sensing time.