Channel Emulator-Based Experimental Measurements for Spectrum Sensing in IoT Networks

Abstract

The rapid expansion of Internet of Things (IoT) applications requires reliable evaluation frameworks capable of reproducing realistic radio-frequency (RF) environments. One of the main challenges is the limited availability of spectrum caused by the growing number of connected devices. This letter presents an experimental platform for assessing RF spectrum-sensing techniques in IoT networks using software-defined radios integrated with a Keysight PROPSIM F8 channel emulator. The platform employs tapped-delay-line channel models to accurately reproduce multipath fading, Doppler effects, and delay spread under controlled laboratory conditions, enabling real-time and reproducible RF-level performance evaluation. Experimental results obtained for 5 G NR and LTE scenarios demonstrate that IoT devices can effectively monitor spectral occupancy for cognitive radio IoT systems, while the proposed emulation framework significantly reduces the cost, time, and complexity associated with field testing. Overall, the work provides a practical and standardized testbed for the evaluation of spectrum-sensing strategies in next-generation IoT deployments.