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Vanderbilt team wins $750K with AI to manage RF spectrum

Feb. 7, 2019, 4:37 PM

Vanderbilt team MarmotE cleared Phase 2 of the U.S. Defense Advanced Research Projects Agency’s Spectrum Collaboration Challenge held in December at the Johns Hopkins University Applied Physics Lab.

With no real estate left to expand the radio spectrum, DARPA’s challenge seeks machine-learning algorithms to sort out frequency priorities based on urgency – emergency and critical safety scenarios in real time – and to cooperate rather than compete for bandwidth.

By demonstrating that their AI could make more connections in a shared radio frequency spectrum environment without degrading other broadcasters in the process, MarmotE was one of six teams each awarded a $750,000 prize. The Vanderbilt team, which led 10 teams in Phase 1 competition in December 2017, came in second.


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