Cooperative Spectrum Sensing in Cognitive Radio Networks

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Resource Overview

This project analyzes the performance of cooperative spectrum sensing with enhanced energy detectors. Cognitive radios (CRs) employ improved energy detection algorithms to determine primary user (PU) presence. The implementation evaluates total probability of error across varying numbers of CRs under different SNR conditions, with a relative threshold set at 10 dB. Key aspects include collaborative decision fusion and energy detection optimization.

Detailed Documentation

In this project, we investigate the significance of cooperative spectrum sensing and enhanced energy detector performance in cognitive radio systems. Cognitive radios (CRs) utilize improved energy detection algorithms to determine the presence of primary users (PUs). Our implementation involves extensive testing across various scenarios under different signal-to-noise ratio (SNR) conditions. The energy detection algorithm computes received signal power and compares it against dynamic thresholds. We observe notable variations in the total probability of error for CRs when the relative SNR threshold is set at 10 dB. These findings, obtained through Monte Carlo simulations and decision fusion techniques, hold substantial importance for advancing research and optimizing cooperative spectrum sensing methodologies. The code structure incorporates collaborative decision-making through hard/soft combination rules and threshold optimization algorithms.

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