Identify the user presence by GLRT and NP detection criteria in cognitive radio spectrum sensing

Abstract

SummarySpectrum sensing in cognitive radio networks is vital and is used for identifying the user presence or absence in the available spectrum. Energy detection and matched filter detection are the few methods to identify the user presence in the spectrum. There are various authors that proposed their research on spectrum sensing using matched filter detection with fixed threshold and predefined dynamic threshold. In this paper, authors proposed the novel matched filter detection method with dynamic threshold by using generalized likelihood ratio test (GLRT) and Neyman Pearson (NP) observer detection criteria. Due to which the probability of detection (PD) is increased, probability of false alarm (Pfa) and probability of missed detection (Pmd) has been reduced when compare with the existing methods. The results are simulated using MATLab Software and also plotted the receiver operating characteristic (ROC) curve for estimation of the receiver sensitivity.