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AI-Driven Spectrum Sensing for Cognitive Radio Networks in Dynamic IoT Environments

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The framework enhances spectrum sensing and efficiency in IoT, suggesting AI can optimize cognitive radio networks.

A 25–40% increase in detection and spectrum efficiency was achieved using the new AI-driven framework.
The approach incorporates deep reinforcement learning and convolutional neural networks for better context sensitivity.
Simulations were conducted across varying IoT scenarios, including different SNRs and interference levels.
The framework shows adaptability in changing channel conditions, indicating practical applications for future wireless networks.

R. Dhivya (2025) studied this question.

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