CR Cooperative Spectrum Sensing Simulation

This paper presents a comprehensive simulation study of CR cooperative spectrum sensing and perception algorithms with detailed investigation and analysis. We begin with an in-depth discussion of the fundamental concepts and principles of CR cooperative spectrum sensing through a systematic literature review. Subsequently, we design a complete simulation framework comprising multiple stages such as data acquisition, signal processing, and algorithm implementation, with detailed explanations and analysis for each component. The simulation architecture includes key modules for signal generation using MATLAB's communication toolbox, energy detection algorithms with threshold optimization, and collaborative decision fusion mechanisms. Through rigorous evaluation and comparative analysis of simulation results, we validate the effectiveness and performance advantages of our proposed sensing algorithms. Furthermore, we conduct sensitivity analysis on various simulation parameters, including detection thresholds, signal-to-noise ratios, and collaboration weights, to investigate their impact on simulation outcomes using parameter sweep techniques. Our research not only provides comprehensive insights into CR cooperative spectrum sensing simulation methodologies but also offers valuable references and guidance for further optimization and enhancement of perception algorithms through systematic performance benchmarking.