Today we design communication networks using mathematical models that describe components of the system that affect end-to-end performance. As wireless links become more highly variable, and system components become harder to model, this approach is losing ground. A team of students led by Dr. Robert Calderbank, Dr. Christ Richmond, Dr. Lingjia Liu, Dr. Jeff Reed, and Carl Dietrich will develop machine learning (ML) algorithms that take advantage of special features of new waveforms proposed for 6G wireless communication. The team will be highly interdisciplinary, and will include students from Virginia Tech familiar with wireless communication, as well as students interested in machine learning. Students will design experiments, collect data, and analyze over the air performance, some working onsite using Virginia Tech’s CORNET testbed, some virtually using CORENT-based remote lab experiments. The team will present their findings to clients at the Air Force Research Lab in Rome, NY.
Project Leads: Robert Calderbank, Christ Richmond, Lingjia Liu, Jeff Reed, and Carl Dietrich
Project Managers: Charles Connors and Akshay Bondre
Watch the team’s final presentation below:
