Due to recent increases in mobile broadband services by consumers, the Federal Communications Commission (FCC) is compelled to make more spectrum available for commercial use. The FCC spectrum-service rulemaking process does not formally assess risk of interference, apply statistical distributions, or recommend coexistence testing. The methodology developed in this dissertation proposes a framework that applies risk, statistics, and coexistence testing and demonstrates how spectrum regulatory decision-making processes would benefit from using a more technically defensible approach. Allowing new systems into a spectrum band can cause interference to the operating incumbent users but preventing new commercial spectrum systems can have negative economic and technological repercussions. Therefore, carefully assessing the effects of a more heavily used spectrum by treating analytical spectrum coexistence testing metrics as distributions can lead to more information-based, data-driven decision making.

When using risk assessments, regulators’ decisions will improve to include results from well-engineered and transparent spectrum coexistence testing accounting for measurement uncertainties with translations to real-world deployments by accounting for all applicable variabilities.