Using FPGAs for Spectrum Sensing and Modulation Recognition

Project Objective

This project seeks to use machine learning to recognize different wireless devices. The project will use software defined radios (SDR) to record various devices, such as iphones, bluetooth earbuds, and Wifi laptops. These recordings will become the training data to a set of neural networks. The second part of the project will quantify the accuracy of the neural networks in classifying various device types based on their RF signatures.

Who We Are

Ryan Davis
Class of 2021
Rutgers University
Computer Engineering and Computer Science


Zhuohuan Li
Class of 2020
Rutgers University
Computer Engineering



Sid Mandayam
Class of 2022
Rutgers University
Computer Science and Mathematics

Reading Material

• ​Overview of FPGA architecture (especially for Xilinx devices), and comparison between FPGA and CPU
• ​Overview of I/Q Communication Theory
• ​Artificial WiFi Packet Generation
• ​Matched Filter Demodulation

Week 1 Activities

• Get ORBIT/COSMOS account and familiarize oneself with the testbed procedures
• Learn about FPGAs
• ​Presentation 1

Week 2 Activities

• Write a UDP client / server in Go
• Generate IQ samples for IEEE 802.11 WiFi packets
• ​Presentation 2

Week 3 Activities

• Rework UDP client / server to work with Go to Verilog compiler
• Transmit and receive generated WiFi packets using the USRPs on the Grid
• ​Presentation 3

Week 4 Activities

• Automate data collection on the Grid
• Learn more about Go lang
• ​Presentation 4

Week 5 Activities

• Begin looking in to matched filters
• Finish data collection on the Grid (a lot of debugging)
• ​Presentation 5

Week 6 Activities

• Matched Filters in MATLAB
• Collect data
• ​Presentation 6

Week 7 Activities

• Dataset documentation / Big metadata file
• Matched Filters in Go

Final Presentation