Investigating Spectrum Sensing in CR-IoT Networks Using Real IoT Signals

Abstract

The expansion of the Internet of Things (IoT) has considerably intensified the demand for radio spectrum, which remains a limited and highly valuable resource. Cognitive Radio (CR) technology provides an effective approach by enabling the dynamic identification of unoccupied frequency bands and enabling opportunistic spectrum access, thus improving spectral efficiency. This paper addresses the problem of spectrum sensing in Cognitive Radio-based IoT (CR-IoT) networks using real IoT signals transmitted by LoRa modules and captured with an RTL2832U software-defined radio receiver. Energy detection is employed as the sensing method due to its low computational complexity and suitability for unknown signals. The effectiveness of the proposed method is assessed using Receiver Operating Characteristic (ROC) analysis, highlighting its ability to reliably distinguish between occupied and idle frequency bands. The results confirm the feasibility of deploying energy detection-based CR-IoT systems in real-world scenarios, providing a practical foundation for future opportunistic spectrum access techniques in IoT networks.