Towards Efficient Spectrum Management: A Data-driven Assessment Framework for Local Licensing

The emerging demand for localized private networks, tailored to specific and diverse use cases, has triggered growing attention to the development of local spectrum licensing approaches that depart from traditional schemes used for broad coverage. In particular, there is a significant need for forward-looking quantitative studies to inform technical choices and ensure that licensing conditions are aligned with overarching goals, such as supporting high spectrum re-use across potentially dense network deployments. Addressing a gap in the current research literature, we introduce a novel data-driven framework to assess the potential effectiveness of local spectrum licensing schemes from a regulatory viewpoint. This approach leverages real-world data to emulate prospective local deployment scenarios, capturing important geographic details such as high-demand market areas, realistic industry locations, and high-resolution clutter information. We discuss the practical application of the framework to a case study focused on the 3.9 GHz band in Canada. Using this case study, we demonstrate the merits of the approach, highlighting the importance of incorporating contextually relevant geospatial datasets to better inform local licensing regulations.