MATLAB Code for Cognitive Radio: Binary Information Implementation

This documentation discusses the implementation of binary information processing in MATLAB code for cognitive radio systems. The code implements a cooperative spectrum sensing scheme where both primary and secondary users participate in spectrum detection. The algorithm utilizes energy detection techniques where received signal power is compared against predefined thresholds to generate binary decisions (1 for occupied, 0 for free spectrum). Key MATLAB functions implemented include signal energy calculation using fft() and abs() operations, threshold determination through statistical analysis of noise floors, and decision fusion algorithms for cooperative sensing. The cooperative scheme employs hard decision combining where multiple users' binary decisions are logically combined (AND/OR rules) to improve detection accuracy. This technique enables more efficient utilization of available spectrum resources, which is crucial in today's wireless communication landscape. The MATLAB implementation allows researchers to simulate various scenarios including different numbers of cooperative users, signal-to-noise ratio conditions, and fusion rules. By adjusting parameters like detection thresholds and cooperation strategies, engineers can optimize system performance metrics such as probability of detection and false alarm rates. Cooperative sensing significantly enhances system performance by reducing interference through better spectrum awareness and increasing overall network throughput. The binary decision-making framework provides a foundation for developing adaptive cognitive radio systems that can dynamically respond to changing environmental conditions and traffic demands. This MATLAB code serves as an essential tool for prototyping and validating next-generation wireless communication systems with cognitive capabilities.