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The Internet of Things (IoT) is a transformative technology that enables vast devices to connect to the internet and exchange data. Rapid spectrum usage in wireless networks can lead to inefficiencies, particularly in terms of energy consumption. To address the challenges of spectrum scarcity and interference in the rapidly growing Internet of Things (IoT) ecosystem, we propose a Cognitive Radio-based Internet of Things (CR-IoT) framework. This approach integrates Cognitive Radio (CR) technology into IoT devices, allowing them to intelligently manage spectrum resources and ensure efficient, interference-free communication. The simulation results authenticate the effectiveness of the proposed algorithm for the Cognitive Radio-based Internet of Things (CR-IoT) system. The proposed algorithm increases the CR-IoT system throughput by 95% compared to the conventional scheme IEEE 802.22 standards under varying Signal-to-Noise Ratio (SNR) conditions.

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A Novel Optimized Energy Detection for Cognitive Radio-Based IOT: A Throughput-Centric Approach

  • 会议论文

  • 发表日期：

    2026年

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  • B. Sreekantha,
  • V. Mahalakshmi,
  • S. Shruthi

摘要

The Internet of Things (IoT) is a transformative technology that enables vast devices to connect to the internet and exchange data. Rapid spectrum usage in wireless networks can lead to inefficiencies, particularly in terms of energy consumption. To address the challenges of spectrum scarcity and interference in the rapidly growing Internet of Things (IoT) ecosystem, we propose a Cognitive Radio-based Internet of Things (CR-IoT) framework. This approach integrates Cognitive Radio (CR) technology into IoT devices, allowing them to intelligently manage spectrum resources and ensure efficient, interference-free communication. The simulation results authenticate the effectiveness of the proposed algorithm for the Cognitive Radio-based Internet of Things (CR-IoT) system. The proposed algorithm increases the CR-IoT system throughput by 95% compared to the conventional scheme IEEE 802.22 standards under varying Signal-to-Noise Ratio (SNR) conditions.