Spectrum Sensing Problem Analysis under Rayleigh Channel Conditions

In this paper, we provide a detailed examination of spectrum sensing problems and corresponding solutions under Rayleigh channel conditions. Our implementation employs Monte Carlo simulation methods to conduct extensive experimental trials, where we simulate wireless signal propagation characteristics using Rayleigh distribution models to mimic real-world fading environments. The experimental framework involves generating random channel instances and statistically analyzing detection performance metrics. Through these simulations, we have derived significant conclusions and observations regarding detection probability, false alarm rates, and threshold optimization. Additionally, we propose several enhancement strategies and optimization techniques, including improved threshold adaptation algorithms and signal processing methods, to further elevate spectrum sensing performance and effectiveness. These research findings carry substantial importance for enhancing capacity and efficiency in wireless communication systems, providing valuable guidance for future developments in communication technologies.