Hongbin Li Awarded $600K from National Science Foundation for His Work on Radio Frequency Sensing
The electrical and computer engineering professor is creating new algorithms to enable radio devices to “see around corners”
Hongbin Li, Charles and Rosanna Batchelor Memorial Chair Professor in the Department of Electrical and Computer Engineering at Stevens, is looking to solve a problem that has existed in the radio frequency (RF) sensing discipline for years: how to see something through an obstacle.
Li recently received a $599,986 grant from the National Science Foundation for his project, “Ubiquitous RF Sensing with Smart Metasurfaces.”
Radio frequency sensing is becoming increasingly pervasive due to the proliferation of wireless communications. The upcoming WiFi standard IEEE802.11bf, arriving in 2024, enables wireless devices to essentially function as radars, capable of sensing their surroundings and determining the position of nearby objects. However, these transmitters and signal receivers currently need to have uninterrupted space in between them, which is not always possible in surveillance environments. Li’s project seeks to apply RF sensing in a revolutionary way that solves this problem.
Seeing and not seeing
“RF sensing is fundamentally limited by the line of sight,” explained Li. “RFs can be easily blocked by many objects, especially if you are working on specific frequencies.”
Some frequencies can be blocked by just a human being walking in front of the sensor. This interference makes it difficult to find the source of the signal.
“In a lot of environments, such as urban or indoor environments, you have buildings, walls, etc. It's much more complicated than an open field,” continued Li. “This particular project is dealing with how you can overcome that limitation, to be able to see and find out specific information about the source around the corner.”
Currently, the field distributes RF transmitters and receivers across a surveillance area so that a target can be observed by at least one transmitter-receiver pair. Unfortunately, such a distributed RF sensing system is bulky, expensive, operationally burdensome, and environmentally unfriendly due to excessive RF radiation.
Li’s three-year project seeks to develop an alternative distributed RF sensing paradigm that can effectively “look” around a corner by leveraging reconfigurable intelligent surfaces (RIS).
RIS are thin, flat structures comprising numerous small, low-cost metamaterial elements (or materials artificially engineered to have certain properties) that can be independently adjusted to control the reflection of incident RF signals. Like wallpaper, RIS can cover parts of buildings, walls and ceilings, allowing RF engineers to proactively customize the radio environment based on specific needs. RIS-aided RF sensing can also be utilized 24 hours a day, as it is light-independent.
Many applications
RIS-aided RF sensing technology could be applied in multiple ways by industry and personal consumers.
Li points to an example of assisted living: By using this technology for fall detection, behavioral monitoring, or a navigation aid for visually impaired, these environments can be made safer. RF, if it could be used around corners, is ideal for such applications in indoor environments. It is also attractive because of its privacy-preserving nature. There is no video element to RF signaling like there would be with a 24 hour camera system.
“People may have privacy concerns. An RF device only sees RF echoes of the object, not an image, so it has advantages over an optical sensor like a camera,” explained Li.
Other application examples are military sensing and building security.
Complex and exciting
Li’s team for this project will consist of him, his Ph.D. students, and potentially some postdoc associates. In the summer, he also plans to bring on undergraduate and high school students.
“It can be fun for the students, and they can also help the project with some different aspects,” said Li.
The work will advance fundamental theories of and practical methods for RF sensing aided by RIS. Research outcomes of this project will have the potential to be integrated with future wireless networks, empowering service providers to offer intelligent RF sensing and communication services to their customers.
But for Li, the work is enough in itself. “I like it because it's challenging, mathematically challenging,” said Li, “and I'm happy that I can use my knowledge, my skill, my research, to help to develop these applications.”