Georgia Tech and Collaborators Receive Grant from The Rockefeller Foundation to Improve Understanding of the Mobile Broadband Experience

While cellular networks are a key method for internet access, millions of Americans in rural communities and on tribal lands lack basic connectivity access, affecting their ability to search for jobs, access healthcare, and participate in educational opportunities. To make connectivity more equitable, researchers at the Georgia Institute of Technology are developing open-source software to empower citizens to report on cellular network quality and places without any connectivity.

With a new grant from The Rockefeller Foundation, combined with funding from the National Science Foundation, researchers aim to create CellWatch, a technology ecosystem comprised of a mobile application for network measurements, a community planning dashboard and map, and a cellular quality prediction tool. CellWatch will enable everyday people to take connectivity measurements and merge their data with others in their community. This will allow communities to build maps of coverage and challenge cellular provider claims of coverage that are often misrepresented across Federal Communications Commission’s (FCC) maps, preventing communities from applying to available federal funding. The goal is to eventually have informed machine learning algorithms and statistical analysis be able to predict the quality of service in other areas that have not yet been measured and empower communities to improve their own cell coverage.

“Mapping mobile broadband turns out to be a very hard technical problem because quality of coverage depends on complex factors, not just how close you are to a tower,” said Ellen Zegura, a professor in the School of Computer Science.

Zegura is one of three principal investigators on the grant. Her collaborators include Elizabeth Belding, a computer science professor at the University of California, Santa Barbara, and Morgan Vigil-Hayes, an assistant professor in computer science at Northern Arizona University. At Georgia Tech, Scott Robertson in the Institute for People and Technology is leading the software development effort and Yao Xie, an associate professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), will be doing machine learning and statistical modeling.

Connectivity Complications

Understanding cell coverage and quality is difficult. The FCC requires all network providers report their coverage areas, but provider maps generally overestimate where coverage exists. While the FCC makes the provider coverage data available to the public, it’s notoriously inaccurate.

It’s even harder for everyday customers to figure out. To challenge a provider’s coverage claim, the FCC has a 100 page document detailing its requirements for citizen reporting including breaking down the coverage grid into hexagons and requiring citizens submit data from multiple hexagons to prove an area is lacking service. There are also requirements for the mix of positive and negative measurement results and the time of day of measurement.

“There’s a huge gap between the FCC requirements document and what regular people understand about connectivity and quality,” Zegura said. “Our goal with CellWatch is to empower everyday citizens to get involved in advocating for high quality internet to their communities to increase access to services, employment, health, and education.”

Creating CellWatch

The researchers involved intend CellWatch to make it accessible for citizens to map their own networks and challenge the FCC through CellWatch’s three-prong project:

• CellWatch Mobile Application: The Android measurement app will be built to comply with FCC requirements so users can successfully challenge provider coverage claims. A backend database will maintain data security and allow aggregation of measurements from different sources.
• CellWatch Community Coordination Tool: This interactive dashboard and map will aid citizens in organizing campaigns to challenge providers while meeting FCC requirements.
• CellWatch Prediction: Machine learning algorithms will predict mobile broadband performance using data collected by CellWatch tools and other public datasets.

All tools will be publicly available and open source to enable access for everyone. Ultimately, CellWatch’s goal is let citizens into the reporting process to democratize coverage and eventually collect enough data that the process can be automated.

“It's hard to know where there's coverage, and you're never going to measure everywhere,” Zegura said. “But if you have taken measured data in some places, you can use machine learning and statistical analysis to make predictions in new locations.”

The information won’t just aid citizens but can also be used to help allocate federal funding to add infrastructure where and when needed. The project is just the start of ensuring all of America has access to reliable network coverage and doesn’t miss out on any opportunities. Out of network will be a thing of the past.