Wireless and optical communications expert receives NSF CAREER award to evaluate analog radio-over-fiber technology.
SHARE
Radio Waves Riding on Optical Fibers
Since joining Duke University in 2021, Tingjun Chen, the Nortel Networks Assistant Professor of Electrical and Computer Engineering (ECE), has built a promising research portfolio exploring the limits of both wireless and fiber-optic technologies.
Thanks to a collaboration with the Office of Information Technology (OIT), Chen has rare access to a live fiber testbed that connects Duke’s East and West campuses with the Chesterfield Building in downtown Durham and also plugs into broader fiber networks in the Triangle. Fiber networks reaching this size are usually owned by telecommunications and tech giants, who use them for proprietary means.
Tingjun Chen has built a promising research portfolio exploring the limits of both wireless and fiber-optic technologies.
Now, Chen is poised to continue expanding his fiber research. With funding from a five-year, $600,000 NSF CAREER award, he will study the performance of sending analog radio waves directly across fiber-optic cables, which might help telecommunications infrastructure meet rising data needs in the future.
“Laying a new fiber network is extremely costly, so we want to get more capacity from the fiber in the ground by multiplexing different types of signals—light, radio or quantum— on the same cable,” Chen said.
Laying a new fiber network is extremely costly, so we want to get more capacity from the fiber in the ground.
Tingjun ChenNortel Networks Assistant Professor of Electrical and Computer Engineering
Going from Digital to Analog Radio-Over-Fiber
Although we rarely stop to think about it, there is a complex infrastructure of wires, base stations and data centers that support the endless capabilities of modern smartphones.
To send or receive data, your phone sends radio signals to base stations scattered around the country. The base stations convert those analog signals into data packets comprising digital zeros and ones, then send those packets in the form of light pulses along fiber-optic cables—long strands of glass tubes—to edge and regional data centers.
This protocol, known as digital radio-over-fiber (DRoF), is a robust system employed by modern 5G networks. Chen, however, is thinking about the future. With growing user populations, data-hungry AI products and connected smart cities, DRoF may not be able to support data transmission 10 or 20 years down the road.
Chen’s lab studies the performance of several types of classical and quantum information sent over field-deployed fiber.
With his CAREER award, Chen will study analog radio-over-fiber (ARoF), which would send data in the form of radio signals over the fronthaul fiber, the connection between the base station and the data center. Think of it as a radio wave directly hitching a ride on top of a laser.
Each technology comes with pros and cons, but the biggest benefits of ARoF are that it simplifies the base station architecture and improves energy and spectral efficiency. If ARoF was adopted, digital signal processing would shift from individual base stations to the data centers, allowing for greater computing power and sharing of heterogeneous computing resources.
Think of analog radio-over-fiber as a radio wave directly hitching a ride on top of a laser.
“The ARoF technology can handle much more bandwidth than its digital counterpart, and we’re not currently maximizing the capabilities of fiber,” Chen said. “While it is not a new technology, ARoF hasn’t been thoroughly studied for and co-designed with telecommunication networks, which is what we aim to explore with the support of this NSF CAREER award.”
Duke’s fiber network with a large footprint will be instrumental to the success of Chen’s research.
“This will give us realistic environments to test our technologies and see how the real world affects radio and light signals over fiber,” Chen said.
The NSF- and DHS-funded institute attracted visitors from industry and government to showcase Duke’s leadership in artificial intelligence and edge computing.