Simulation of Energy Detection Method in Cognitive Radio

In this paper, I will conduct a simulation of the energy detection method in cognitive radio and provide its source code along with a detailed explanation. The simulation involves implementing key signal processing algorithms including signal sampling, energy calculation using FFT-based power spectrum estimation, and threshold-based decision logic to detect primary user presence. I will elaborate on the simulation methodology step by step, covering the MATLAB/Simulink implementation structure, critical functions for signal generation and detection, and parameter configuration for different SNR scenarios. The code architecture includes modules for signal preprocessing, energy computation using periodogram methods, and hypothesis testing with Neyman-Pearson criteria. Additionally, I will analyze the method's advantages in computational simplicity and hardware implementation feasibility, while addressing limitations such as performance degradation under low SNR conditions and susceptibility to noise uncertainty. To enhance performance, I will propose improvements including adaptive threshold optimization algorithms and hybrid detection techniques combining feature detection. Finally, I will discuss relevant research domains like dynamic spectrum access networks and emerging applications in 5G/6G systems, providing practical implementation insights for researchers and engineers.