In 2016, DARPA rolled out a new Grand Challenge, the Spectrum Collaboration Challenge (SC2), with the goal of ensuring that the exponentially growing number of military and civilian wireless devices have ready access to increasingly crowded electromagnetic spectrum when needed. SC2 was designed to encourage researchers to develop smart systems that collaboratively, rather than competitively, adapt in real time to the fast-changing, congested spectrum environment—redefining the conventional spectrum management roles of humans and machines to maximize the flow of radio frequency (RF) signals.
The primary goal of SC2 was to imbue radios with advanced machine-learning capabilities so that they could collectively develop strategies that optimize use of the wireless spectrum in ways not possible with today’s intrinsically inefficient approach of pre-allocating exclusive access to designated frequencies.
SC2 unfolded over a three-year period with two preliminary competitions preceding a live finale that occurred in October 2019. Team GatorWings from the University of Florida won first place in the competition, followed by Team MarmotE, comprised of current and former Vanderbilt University researchers, in second place, and Team Zylinium, a three-person start-up with expertise in software-defined radios and AI, in third place.
