Plug and Play Flexible Signal Classification and Processing System

With an expanding wireless revolution fueled by Internet of Things (IoT), autonomous cars, and software defined radios (SDRs), the need to monitor the wireless environment in real-time is becoming paramount in a variety of important applications. In this work, we present a scalable plug and play real-time signal classification and processing architecture motivated by these important applications. While many existing works focus on specific signal classification techniques, our focus is on providing a robust and flexible architecture that enables classification of a wide range of signals. Our distributed architecture allows the processing components to be mixed and matched in a variety of configurations to best suit the classification and processing requirements of the desired application. We describe how our architecture can be used in a variety of scenarios to detect unauthorized wireless activities including airports, power substations, and shared wireless spectrum. We build a prototype implementation of our architecture that successfully demonstrates its practicality and utility. We evaluate our system in terms of both processing and networking throughput. We show that we can process up to 20 MHz of bandwidth from a HackRF One software defined radio as 32-bit IQ samples and that over 99.99% of the samples at that sample rate can be transferred between components on the same machine during a 15 minute period.