Comparison Analysis of Static and Dynamic Thresholds for Conventional Cognitive Radio Spectrum Sensing Methods

In cognitive radio networks, spectrum sensing is pivotal for efficient utilization of the radio frequency spectrum. This paper presents a comparative analysis of static and dynamic thresholding techniques applied to two conventional spectrum sensing methods in cognitive radio systems; energy based and matched filter-based sensing methods. These two methods are implemented based on conceptual theories and review literature. The study evaluates the performance metrics such as probability of detection (PD) and probability of false alarm (PFA) for the two thresholds scenarios under additive white noise conditions. Through these simulations based on the analytical models, it was found that the threshold choice performance depends on the method selected. In energy-based method, PD of 20 % is achieved at signal-to-noise ratio (SNR) of -10 dB for dynamic threshold for energy-based method when compared to 45 % for static threshold. The opposite was observed for matched filter-based method as the PD of dynamic threshold was better. The findings highlight the trade-offs between simplicity and adaptability in threshold selection, aiding in informed decision-making for spectrum sensing design in cognitive radio networks.