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Reinforcement Learning Application for Joint Communications and Radar Sensing

This project has developed a testbed for evaluating novel algorithms for spectrum sensing in integrated sensing and communication applications. Primary and secondary users must be able to share channels and switch between them as necessary. Algorithms facilitating these processes are being researched and/or developed. However, a generic testbed currently doesn’t exist where these algorithms can be tested against simulated signals and this project aims to remedy this issue.

Team Members

Sean Paul Gras
Shane Hauser
Bharath Kaimal
Amy Lee
Hans Matthew Robles

Semester