Comparative Study of Spectrum Sensing Techniques for Cognitive Radio Systems in Noisy Environments

Abstract

Within the realm of cognitive radio systems, spectrum sensing is an essential component that enables dynamic access to underused spectrum bands while simultaneously coexisting with core users. Due to the existence of a wide variety of interference sources and noise types, however, the implementation of spectrum sensing techniques in noisy environments presents a considerable difficulty. Even when there is noise present, spectrum sensing may be carried out in an efficient manner according to the innovative hybrid technique that is shown in this paper. A variety of values of signal sample sizes and noise uncertainties are taken into consideration in the analysis of the study. Energy Detection (ED), Covariance Absolute Value (CAV), and Joint Estimation mechanism are the three mechanisms that are subjected to the comparative examination. When compared to the conventional methods, the findings demonstrate that the proposed work is superior.