In the battlefield, it’s essential that soldiers can reliably and clearly communicate with each other. To do so, they need a dependable and robust wireless network. Edmund Yeh, professor in the College of Engineering, is leading Northeastern’s work in a new research project to advance wireless communication technology specifically in order to handle challenging, uncertain environments.
The research—a collaboration between Northeastern, Raytheon BBN Technologies, and the Massachusetts Institute of Technology—is funded by a four-year, $10 million grant from the Defense Advanced Research Projects Agency, a branch of the U.S. Department of Defense.
“This is definitely an exciting project because it’s fairly large,” said Yeh, whose own research focuses on the optimization of wireless networks. “We have very good partnerships, in the sense that Northeastern and MIT will be doing the fundamental science while Raytheon BBN will be developing the software.”
The goal is to design an adaptable, energy-efficient wireless communication network that will reduce delay between message transmission and reception. The plan is to decentralize the system—a feature that will make the entire network more resilient in the face of uncertainty.
An example Yeh offered is soldiers, who may sometimes have access to a fixed signal station on an armored vehicle, but often need to communicate in the field without that nearby transmission point.
“Soldiers have mobile devices that are battery-constrained, so you aren’t going to want to spend a lot of energy transmitting information,” Yeh said.
Network coding is one of Yeh’s research specialties and will figure heavily in the project. It’s a process by which information streams are mixed together, coded together, then unmixed and sent to many different receivers. “Information isn’t like water, where you send it through separate pipes to get to separate places,” he explained, noting that the research collaborative will work to leverage Northeastern’s expertise in wireless networks. “With information, it’s better and more efficient to mix those streams, perform algebraic operations on them, then un-mix them later.”