Rose Hu, a Utah State University professor of electrical and computer engineering and the associate dean for research in the College of Engineering, recently received a $165,000 grant from the National Science Foundation to reshape the future of next-generation wireless communication technologies.
This grant is part of a $500,000 collaborative project to explore a systematic approach to accelerate communication and computation-intensive tasks such as channel state information processing — how a signal travels from transmitter to a receiver — by orders of magnitude in massive multiple-input, multiple-output communication systems. These systems typically have devices and nodes with hundreds or even thousands of antennas. This project that Hu is the lead researcher for will lay a foundation for enhancing data rate and energy efficiency and spectral efficiency in next-generation wireless networks.
“We are designing what we call lightweight artificial intelligence,” Hu said. “We can use this to greatly reduce the training time it takes artificial intelligence to make a decision by extracting the most important information.”
Artificial intelligence, or AI, and machine learning are an important part of building powerful wireless communication networks. Currently, the massive amount of data these networks require is centralized, which slows down the decision-making process of systems. Through decentralization, optimization of data features, and simplification of AI structures, lightweight artificial intelligence has the potential to greatly reduce the time it takes for tasks to occur without losing accuracy.
“Many communication processing tasks need to be executed in real-time in the range of milliseconds,” Hu said.
The research Hu and her colleagues from the University of Nebraska, Lincoln, and the University of Dayton are working on will consist of theoretical analysis and performance evaluations on a variety of new algorithms.
“I’m very excited because this contributes to the road map of my long-term wireless communication and networking research by utilizing the power of ubiquitous AI and machine learning,” Hu said.
Last year, Hu also received a $250,000 National Science Foundation grant as part of a $500,000 collaborative project for secure and efficient wireless edge communication and computing research. She is currently working on a proposal for another larger grant from the foundation.
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