AI may be better for detecting radar signals, facilitating spectrum sharing

In a new paper, NIST researchers demonstrate that deep learning algorithms -- a form of artificial intelligence -- are significantly better than a commonly used, less sophisticated method for detecting when offshore radars are operating. Improved radar detection would enable commercial users to know when they must yield the so-called 3.5 Gigahertz (3.5 GHz) Band. In 2015, the FCC adopted rules for the Citizens Broadband Radio Service (CBRS) to permit commercial LTE (long-term evolution) wireless equipment vendors and service providers to use the 3.5 GHz Band when not needed for radar operations. Companies such as AT&T, Google, Nokia, Qualcomm, Sony and Verizon have been eager to access this band (between 3550 and 3700 MHz) because it will expand product markets and give end users better coverage and higher data rate speeds in a variety of environments where service is traditionally weak. NIST helped develop 10 standard specifications that enable service providers and other potential users to operate in the 3.5 GHz Band under FCC regulations while assuring the Navy that the band can be successfully shared without RF interference.