Hardware integration of preamble based 802.11a Wi-Fi frame location for USRP radios

Internet of Things (IoT) refers to a network of devices that can exchange information over the internet, and its deployments are projected to reach 30.9 billion by 2025, with most lacking encryption. One solution for these unencrypted devices is to use Specific Emitter Identification (SEI). SEI exploits distinct, native, and unintentional features of a radio’s signal to identify it and enhance wireless network security uniquely. For example, IEEE 802.11a Wireless-Fidelity (Wi-Fi) radio waveforms have a fixed structure that occupies the first 16 microseconds, from which SEI features can be extracted and used to identify the originating radio. By removing the intentional structure from this fixed portion of the signal, we can focus on the emitter’s specific attributes and classify them using techniques such as neural networks. Work in this field involves collecting signals with a software-defined radio (SDR) and processing them separately on a local machine. The objective of this work is to move the processing entirely into the SDR to facilitate real-time, on-site SEI. Ettus Research’s Universal Software Radio Peripheral (USRP) radios use open-source Xilinx FPGAs, such as the Spartan and Zynq lines, allowing users to modify the transmit (TX) and receive (RX) chains to suit their specific needs. Using the onboard FPGA, we can design a pipelined system that locates a Wi-Fi frame on a wireless channel and captures it in real-time entirely in hardware. By defining a process for custom FPGA image development, this work aims to allow any researcher doing their own processing or classification to follow the method to implement their real-time methods.