Spectrum Sensing With Intelligent Reflecting Surfaces

This code simulates spectrum sensing with and without IRSs under different signal conditions.
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Updated 30 May 2023

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This code simulates spectrum sensing in cognitive radio networks under varying scenarios using intelligent reflecting surfaces (IRSs). It considers key parameters, including the signal-to-noise ratio (SNR), noise figure (NF), user traffic intensity, and the distances to the IRSs. The code calculates detection probabilities (Pd) both without the use of IRSs and with two IRSs positioned at different distances. It also considers the gain from an IRS, which depends on the SNR, user traffic, and distance to the IRS. The output is a comparative analysis of detection probabilities against the SNR for different scenarios.

Cite As

Ardavan Rahimian (2024). Spectrum Sensing With Intelligent Reflecting Surfaces (https://www.mathworks.com/matlabcentral/fileexchange/130279-spectrum-sensing-with-intelligent-reflecting-surfaces), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0