This SDRIOTSS project aims to improve awareness of communications in the Radio Frequency (RF) spectrum by capturing Internet of Things (IoT) signals and classifying which signals are present in congested and contested RF environments.
With numbers of wirelessly connected devices increasing, cyber attacks and congestion in the RF spectrum can cause serious issues for mission-critical communications for UK Government departments. Being able to identify and classify IoT signals can improve both cybersecurity and communications efficiencies.
The SDRIOTSS project will utilise a newly released COTS Software Defined Receiver (SDR) system into a Radio Frequency (RF) spectrum survey tool and will involve a combination of hardware developments, signal processing and machine learning outputs on real RF signatures. The objectives for the work focus on the setup of an experimental configuration using cutting edge RF hardware (Xilinx RFSoC), previously developed for radar research, to capture IoT signals. This work will be completed in close collaboration with project user partner Dstl. The origin of the IoT spectrum survey challenge was derived directly from Dstl requirements and inputs on this current capability gap will be provided via close technical partnering on the work.