Efficient Centralized Cooperative Spectrum Sensing Techniques for Cognitive Networks

Wireless Communication is a system for communicating information from one point to
other, without utilizing any connections like wire, cable, or other physical medium. Cognitive Radio
(CR) based systems and networks are a revolutionary new perception in wireless communications.
Spectrum sensing is a vital task of CR to avert destructive intrusion with licensed primary or main
users and discover the accessible spectrum for the efficient utilization of the spectrum. Centralized
Cooperative Spectrum Sensing (CSS) is a kind of spectrum sensing. Most of the test metrics designed
till now for sensing the spectrum is produced by using the Sample Covariance Matrix (SCM) of the
received signal. Some of the methods that use the SCM for the process of detection are Pietra-Ricci
Index Detector (PRIDe), Hadamard Ratio (HR) detector, Gini Index Detector (GID), etc. This paper
presents the simulation and comparative performance analysis of PRIDe with various other detectors
like GID, HR, Arithmetic to Geometric Mean (AGM), Volume-based Detector number 1 (VD1),
Maximum-to-Minimum Eigenvalue Detection (MMED), and Generalized Likelihood Ratio Test
(GLRT) using the MATLAB software. The PRIDe provides better performance in the presence of
variations in the power of the signal and the noise power with less computational complexity.