Collaborative Research: IMR: MM-1A: MapQ: Mapping Quality of Coverage in Mobile Broadband Networks using Latent Gaussian Process Models

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

About 85% of people in the United States own a smartphone and use it to access the Internet on a regular basis, checking e-mail, using video conferencing applications, communicating with a doctor’s office, or searching for an answer to an urgent question. Sometimes these applications work well, and other times they do not. When they do not work well, the problem is often with the mobile broadband cellular network in the place and at the time of use. Unfortunately no one knows completely and accurately where high quality access exists, nor where regions of limited or no access are present. Accurate maps of coverage quality would enable resources to be directed to areas of greatest need, allow long term tracking of progress on the digital divide, and form a building block for new applications that can adapt to network quality. This project aims to create accurate and complete maps of cellular coverage quality by bringing together multiple measurement datasets and creating guidance for new measurements. This collaborative project brings together experts in statistical modeling, machine learning, and mobile networking from Georgia Institute of Technology and University of California, Santa Barbara. The project has two thrusts. The first focuses on creating mathematical models to predict cellular network quality using latent Gaussian processes in novel ways to combine measurement datasets collected with different methodologies. One set of models will consider how coverage quality varies over geographic space; the other will consider how it varies over time. The second thrust focuses on using the predicted coverage quality maps in two key ways, to use the models to create a Quality of Coverage metric that provides useful information to network users, and to use the models to guide in future measurement campaigns so that regions that are not well understood get prioritized. The United States Federal Government and other government and non-government organizations have allocated funding to broaden Internet access. However, because no one accurately knows where high quality access exists (or does not), it is difficult to target investments to communities of highest need. If successful, this work will be able to inform local, state, and federal governments about where investment should be made to ensure all Americans have access to high quality mobile Internet. As a result, residents of these communities will benefit from the educational, economic, and medical benefits that Internet access enables. https://sites.gatech.edu/mapping-broadband/ - this site will contain products of the project, including datasets, models, algorithms, and publications resulting from the work. The website and repository will be maintained for at least five years, from 2022 to 2027. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.