Artificial intelligence, machine learning, and similar technologies (collectively, AI) are poised to transform industries, institutions, and our day-to-day lives.  The past year alone has shown the many ways that these technologies will change how we communicate, function, and obtain and understand information.  While government stakeholders grapple with whether and how to regulate AI, they are also contemplating how to use these technologies to enhance their licensing and supervisory responsibilities.  The FCC is doing just that.  This past week, the FCC released a draft notice of inquiry (NOI) on how to leverage AI to bolster its knowledge and analytic capabilities regarding commercial radiofrequency spectrum usage.  Why?  Publicly available commercial spectrum usage data remain scarce; therefore, the FCC relies on third-party studies when considering new spectrum uses.   

This proceeding will not address the Commission’s underlying spectrum policies or service rules.  It will, however, advance the FCC’s 2023 Spectrum Policy Statement advocating for modern technologies to deepen FCC commercial spectrum usage knowledge in “a cost-effective, accurate, scalable, and actionable manner.”

Current Spectrum Monitoring Data Collection Methods

Obtaining real-time spectrum use data is challenging.  For instance, the Universal Licensing System, International Communications Filing System, and other FCC databases lack real-time licensed spectrum use information.  White space databases and automated frequency coordination systems track available spectrum for secondary use but do not assign users to specific channels.  Recognizing these deficiencies, the FCC authorizes third-party administrators to develop and maintain spectrum access systems for monitoring and coordinating shared uses in one band.  The FCC also conducts speed and drive tests through mobile operators to gather network coverage and broadband speed data.  Despite these efforts, real-time spectrum usage data is unavailable for nearly all spectrum bands.

Other U.S. agencies and international bodies have explored or are exploring similar opportunities.  For example, the National Telecommunications and Information Administration surveys federal spectrum data through its Spectrum Analysis Program and the Institute for Telecommunication Sciences, which recently studied the Citizens Broadband Radio Service.  The National Science Foundation (NSF) and National Institute of Standards and Technology (NIST) have addressed the benefits and challenges of spectrum data with more recent initiatives, including NIST’s assessment of spectrum usage during the COVID-19 pandemic.  

Multiple international bodies are also monitoring spectrum usage.  The International Telecommunication Union has emphasized the role of spectrum monitoring for effective spectrum management and interference resolution.  Its member state administrations operate the International Monitoring System with approximately 400 stations in 81 countries collecting data, sending reports, and publishing summaries regarding spectrum use.  The United Kingdom deploys spectrum detectors throughout the country to help measure and understand spectrum use in particular areas.  Canada’s Communications Research Centre has advanced a prototype system for visualizing spectrum data.  

Taken together, these efforts highlight the importance of data-driven spectrum management domestically and globally.

Comment Areas

In the draft NOI, the FCC seeks input on four areas.

1. Defining spectrum usage.  How should spectrum usage be defined?  What are the benefits and drawbacks of previous initiatives to define, understand, and measure spectrum usage?  Should the FCC break down spectrum usage into components, such as geographic usage, frequency usage, and time usage?  What other radiofrequency engineering metrics beyond the mere presence of a signal at a particular strength could evaluate spectrum uses?  Can spectrum usage metrics be combined to generate a holistic understanding of the radiofrequency landscape?

2. Band-specific issues.  What are best practices, operational considerations, and technical parameters that might correspond to different aspects of spectrum usage across different radio services?  How should the FCC prioritize data collection when each issue or band has its own unique challenges?  Are there comments on the conclusions from the 2016 NSF workshop that support measuring traditional fixed and mobile terrestrial transmitters and bands below 6 GHz?  How should the Commission adapt its research techniques based on licensing and use characteristics for specific bands?

3. Data deliberations.  What data sources could facilitate understanding of spectrum usage?  What are existing data sources?  What are the data-related challenges, such as cost and burden, standardization, and technical accuracy?  What are the benefits and drawbacks of various methods to gather data, including crowdsourcing, external data sources, modeling, and direct observation?

4. Other matters.  What are other practical, technical, and legal concerns for spectrum utilization, including data privacy and security, FCC statutory authority, and digital equity and inclusion considerations?  How should the FCC facilitate and incentivize data sharing?  Should it launch a field monitoring pilot program in the near term to study non-federal spectrum use?  What criteria should it use when examining how other stakeholders (agencies, universities, private entities) could assist with their research and reporting?  Should it issue non-binding guidance in the longer term that may outline best practices for evaluating spectrum usage?

Next Steps

The FCC will consider the draft NOI at its August 3, 2023 open meeting.  To stay engaged with this proceeding or if you have any questions, contact Hogan Lovells.

Update:  the FCC adopted the NOI.  Comments are due October 3, 2023, and reply comments are due November 2, 2023.

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Many thanks to summer associates Jordyn Johnson, Isabelle Dean, and Ryan Campbell for their valuable contributions to this publication.

Authored by George John, Ryan Thompson and Andrew McCardle.