Newswise — For centuries, “open sesame” have been the magic words used to gain access to a cave of treasures. When it comes to the wonders of wireless, there’s only one magic phrase for unlocking the wireless future: “Open Radio Access networks” (O-RAN).
Two Virginia Tech faculty in the Bradley Department of Electrical and Computer Engineering will utilize their wireless wizardry to capitalize on these open networks with funding from the Public Wireless Supply Chain Innovation Fund.
Nishith Tripathi is research associate professor and affiliated faculty for Wireless@Virginia Tech, which is directed by Lingjia Liu, electrical and computer engineering professor, Bradley senior faculty fellow, and founding faculty at the Virginia Tech Innovation Campus.
Tripathi and Liu each received $2 million awards from the $1.5 billion Innovation Fund, which was established by the Biden-Harris administration to develop O-RAN technology and drive a more competitive wireless network market that lowers costs and creates jobs.
As part of the U.S. Department of Commerce’s National Telecommunications and Information Administration (NTIA) and funded by the CHIPS and Science Act of 2022, the Innovation Fund has awarded grants to multiple U.S. universities and companies, all with focuses on the four strategic objectives:
- Promote 5G (and beyond) technologies that are secure and open
- Advance the utilization of open equipment that’s easy to connect with
- Support the integration of networks with multiple brands of equipment
- Identify criteria to decide if equipment follows “open” standards
With each of their individual grants, Tripathi and Liu will focus on all four areas for the fund.
Open network? Open to attacks
O-RAN is the open access version of traditional radio networks that are dominated by a single vendor in a specific geographic area served by a cellular service provider, like the early 4G and 3G networks monopolized by vendors like Nokia, Huawei, and Ericsson. With O-RAN's interoperability – how equipment and software work together on a single network – the wireless world can become a more competitive space from parts to entire networks.
Open networks are full of not only possibilities, but also vulnerabilities, some of which Tripathi will address with his funding.
Because manual testing is inefficient and error prone, Tripathi, plans to tackle making O-RAN more secure in his project, Holistic Cybersecurity Testing Framework for 5G Open Radio Access Networks.
Tripathi’s project will develop multiple testing methods for 5G O-RAN, each with a different focus on vulnerabilities, bugs or attacks, including the following:
- Uncovering vulnerabilities highlighted by radio interface attacks
- Automatic detection of privacy violations that could expose sensitive data
- Creating unique, agile frameworks to discover memory errors or logic flaws in how O-RAN operates
- Automating cybersecurity testing to enhance efficiency and effectiveness
“With the help of this award, we look forward to contributing toward a vibrant, comprehensive, and trustworthy O-RAN ecosystem,” said Tripathi.
He’ll collaborate with Virginia Tech colleague Jeffrey Reed, the Willis G. Worcester Professor in electrical and computer engineering; Vijay Shah, assistant professor at George Mason University; Syed Rafiul Hussain, assistant professor at Penn State University; and Bo Tang, associate professor at Worcester Polytechnic Institute. Additionally, the Commonwealth Cyber Initiative and its O-RAN compliant CCI xG Testbed are playing key roles in the NTIA projects.
Make it faster, better, and more efficient
The future of O-RAN is the ability to bring any device or software to the network and have a secure, seamless connection. But there’s one potential stumbling block: the seamless connection.
Enter Liu, who plans to develop an intelligent testing framework under his grant project, Learning-Based O-RAN Testing.
Building on previous successes with an established neural network, Liu and his team will develop efficient and accurate tests for cellular vendors looking to leverage O-RAN for faster, better, wireless operations. Connecting parts and even other networks to open networks requires each piece to be tested for compatibility, which requires effort, time, and many testing metrics, such as latency – the time it takes for data to travel between two points – or smoothness – consistency and stability of data flow.
For this project, Liu, director of Wireless@VT, is collaborating with Reed, electrical and computer engineering Professor Harpreet S. Dhillon, and Lizhong Zheng, an electrical engineering and computer science professor at the Massachusetts Institute of Technology. They’ll focus on reducing those metrics – from thousands to handfuls – utilizing reservoir computing, a machine-learning approach inspired by how human brains process information.
“The most exciting thing is to see our real-time machine learning and neural network tools applied to O-RAN,” Liu said. “You can do a lot of fantastic theory on paper, but this project will bridge that theory with practice on our real hardware.”
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