Cyclostationary feature based detection using window method in SIMO cognitive radio system

Abstract

With some recent developments in the field of wireless communication at rapid pace, 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 dynamically adapts its parameters and protocols 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, Filter Bank, Eigenvalue based Detection, Covariance based Method, Multiple antenna method and Multitaper Method. In this paper, a spectrum sensing technique is proposed which is based on the cyclostationary spectrum sensing in multiple antenna cognitive radio by Maximal Ratio Combining (MRC) method. Spectral Correlation Density (SCD) is computed by FFT Accumulation Method (FAM) to perform Cyclic Analysis. Simulation results show that CFD for lower SNRs as the proposed scheme can detect the primary user with a probability of 90 percent approximately at −20dB.