SNR Comparison-Based Cooperative Spectrum Sensing with Fusion Center

This article presents a cooperative spectrum sensing algorithm that utilizes signal-to-noise ratio (SNR) comparison at the fusion center. The fundamental concept of this algorithm involves collaborative processing of signals from multiple receivers to enhance detection sensitivity and accuracy. We demonstrate the implementation of a simulation program to model this process, with key components including: 1) SNR calculation modules for individual receivers using signal power estimation functions, 2) Decision fusion logic implementing comparison thresholds, and 3) Performance evaluation metrics for detection probability and false alarm rate. Through analysis of simulation results, we validate the algorithm's effectiveness by examining detection performance under varying SNR conditions and comparing the impact of different parameter configurations. The implementation typically involves MATLAB functions like awgn() for noise addition, pwelch() for power spectrum estimation, and custom threshold optimization routines. This approach enables readers to gain deeper insights into the working mechanism of cooperative spectrum sensing algorithms and understand their practical application for improving signal detection efficiency and accuracy in real-world scenarios.