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How AI Helped the FCC Auction Off $19-Billion Worth of Radio Spectrum

By ­BC Science

June 30, 2017

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Researchers at the University of British Columbia (UBC) in Canada and Stanford University in March organized a $19-billion auction of 84 megahertz of radio spectrum using artificial intelligence (AI).

The team of computer scientists and economists designed and developed a reverse auction solution in which the price was set by how low TV broadcasters were willing to go to turn over their unused airwaves. The implication was that in densely populated areas, broadcasters made more money for their sales, while those in less populous regions were paid less for their spectrum.

The system also factored in other variables, including the number of trades occurring at once and property rights.

The AI-based system may be helpful as countries prepare to sell bandwidth for the future 5G mobile network, while UBC professor Kevin Leyton-Brown says the design could serve as a model for similar auctions even on a much smaller scale.

From UBC Science
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