VT, Amazon Web Services launch Emerging Technology research fellowship

James Dalpino
·2 min read

BLACKSBURG, Va. (WFXR)— The Virginia Tech National Security Institute is working with Amazon Web Services to give 11 undergraduate students and a graduate research assistant experience deploying state-of-the-art machine algorithms to advance machine learning within the ‘cloud’ for wireless communication applications.

This collaboration is part of the Emerging Technology Research Fellowship. This fellowship aims to improve the performance of radio frequency spectrum sensing algorithms by using multiple sensors collaborating through the cloud. Elements of the spectrum sensing process include:

  • Detecting the presence of transmitted wireless signals

  • Estimating the parameters of the detected signals, such as duration, bandwidth, duty cycle, etc.

  • Classifying the parameters of the detected signals, such as Bluetooth, Wi-Fi, Cellular, etc.

  • Fingerprinting the specific radio, or wireless devices, that transmitted the signal

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To identify the process between the sensors and the cloud, the research team is working on developing an approach that will determine what information gets sent to the cloud. They are also working on discovering how to wait for the information based on the learned capabilities of the sensors, and what information should be provided back to sensors to make better decisions in the future. This will prepare undergraduate students for possible careers using machine learning tools in support of national security use cases.

“Our team’s research is fundamentally about how to efficiently perform collaboration between the cloud and the RFML-enabled sensors and how to send the minimum amount of information to the cloud to reduce communication overhead,” said William “Chris” Headley, co-principal investigator and associate director of the institute’s Spectrum Dominance Division. “It’s this well-known tradeoff between how much RFML data you send and the resulting performance, under the consideration of sensors with different capabilities, that is the crux of this work.”

This fellowship was adopted from the Amazon-Virginia Tech Initiative for Efficient and Robust Machine Learning. VT says Amazon Web Services team members have been involved in this project from the beginning, attending meetings to offer feedback and advice, which students have highly appreciated.

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