Automated RF Signal Measurement Algorithms for IoT Applications using Spectrum Analyzers

This paper details the development of algorithms to automate RF signal measurements for Internet of Things (IoT) applications, utilizing a spectrum analyzer and its Python API. Addressing the critical nature of test equipment usage time in laboratory environments, these automation algorithms are designed to maximize productivity. Thereby significantly enhancing measurement reproducibility and precision through the implementation of pre-determined parameters provided by local standards. The system is capable of minimizing human intervention. The software employs a modular, object-oriented structure, ensuring both flexibility and robustness. It provides a Graphical User Interface (GUI) which includes both time and frequency domain measurements, coupled with an instant feedback interface offering all necessary resources to adjust critical spectrum analyzer parameters. Current version of the measurements automation includes report generation besides other usual time and frequency domain parameters such as bandwidth, peak power, average power, total power and duty cycle. The system’s capabilities were validated using test cases including a single-tone sine wave, an arbitrary 256QAM signal, and analyses of Wi-Fi and Bluetooth Low Energy signals. Furthermore, all acquired and processed measurements are automatically integrated into a generated report.