Spectrum Sensing in MIMO Cognitive Radio Networks Using Likelihood Ratio Tests with Unknown CSI

Abstract

Spectrum scarcity increases day by day due to underutilization of spectrum, Cognitive Radio Network (CRN) has been considered as a promising solution for in 5G communication system, as all of the available frequencies are not properly occupied in the spectrum. This is also very common to see that some of the frequencies in band are not utilized and some are overutilized. So the spectrum sensing is necessarily required to improve the accuracy of spectrum utilization and to protect the transmission of primary users. However, the dynamic nature of spectrum makes the sensing as a cumbersome task. In this paper, the problem of spectrum sensing in MIMO cognitive radio networks (CRN) has been considered in the existence of channel state information (CSI) uncertainty and various popular likelihood ratio test (LRT’s)has been suggested and analyzed for spectrum sensing. The expressions for probability of false alarm and probability of detection are also obtained in closed form. Simulation experiments are performed in MATLAB to compare the performance of suggested LRT’s and to identify the optimum LRT for CRN.