This document discusses and compares two spectrum sensing techniques for cognitive radio networks: energy detection and matched filter detection. It analyzes the performance of these techniques based on probability of detection and probability of false alarm under different signal-to-noise ratio levels and fading channel models (AWGN, flat fading, Rayleigh fading). The key findings are that matched filter detection has better performance than energy detection, but requires prior knowledge of the primary signal. Energy detection has lower complexity but performs poorly in low SNR scenarios. Overall, matched filter detection results in lower probability of false alarms compared to energy detection.