Background: Over the next ten years, President Obama’s National Broadband Plan seeks to free up 500 MHz of spectrum for commercial broadband carriers to deploy the next generation of mobile broadband, and DOD radar spectrum is a prime candidate because it is often perceived as underutilized. To cope with potential loss of both radar and communications spectrum, the US Navy is investigating how heterogeneous technologies can coexist and operate simultaneously without causing interference to each other.

Virginia Tech proposed application of machine learning techniques that would allow a radar to survey its spectral environment, characterize the channel access behaviors of the devices in its environment, and develop a frequency hopping pattern that simultaneously minimizes mutual interference while maximizing radar mission objectives. The system will predict when and where spectrum access opportunities will occur, and schedule radar pulses in those predicted slots.

While Virginia Tech focuses on the theory, Shared Spectrum Company will focus specifically on the implementation on the AN/SPY-1 platform, in coordination with the Naval Research Laboratory and NSWC Dahlgren. The Aegis Combat System is one of the Navy’s most advanced integrated weapons systems and uses the AN/SPY-1 radar to track inbound ballistic threats and guide interception weapons to destroy them in a completely automated way. Decreasing interference in the 3.5 GHz band will improve the Aegis performance, particularly in the vicinity of foreign port cities operating commercial WiMAX networks. If successful, both DOD and commercial radar programs can apply the resulting technology to a broad class of spectrum sharing applications.