Deep Convolutional Neural Networks for the NextG Standard

Seminar
Friday, January 21, 2022
EER 3.646

Deep Convolutional Neural Networks for the NextG Standard: Enabling and Experimentally Validating Secure and High-Bandwidth Links

The future NextG wireless standard must be able to sustain ultra-dense networks with trillions of untrusted devices, many of which will be mobile and require assured high-bandwidth links. This talk explores how deep learning, specifically deep convolutional neural networks (CNNs), will play a critical role to enable secure, high-bandwidth links while minimizing complex, upper layer processing and exhaustive search of the state space. First, we describe how device identification can be performed at the physical layer by learning subtle but discriminative distortions present in the transmitted signal, also called as RF fingerprints. We present accuracy results for largest the radio population (over 10K devices) ever reported in the literature as well as datasets collected from community-scale NSF PAWR platforms. Second, we we show how beam selection for millimeter-wave links in a vehicular scenario can be expedited using out-of-band multi-modal data collected from an actual  autonomous vehicle equipped with sensors like LiDAR, camera images, and GPS. We propose individual modality and distributed fusion-based CNN architectures that can execute locally as well as at a mobile edge computing center, with a study of associated tradeoffs. In closing, we provide a glimpse of other systems-centric works that leverage CNNs, such as beamforming with unmanned aerial systems and shaping the wireless environment through reconfigurable intelligent surfaces. 

 

Speaker

Professor
Northeastern University
Prof. Chowdhury is Professor in the Electrical and Computer Engineering Department and Associate Director of the Institute for the Wireless IoT at Northeastern University, Boston. He is the winner of the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE) in 2017, the Defense Advanced Research Projects Agency Young Faculty Award in 2017, the Office of Naval Research Director of Research Early Career Award in 2016, and the National Science Foundation (NSF) CAREER award in 2015. He is the recipient of best paper awards at IEEE GLOBECOM'19, DySPAN'19, INFOCOM'17, ICC'13,'12,'09, and ICNC'13. He serves as area editor for IEEE Trans. on Mobile Computing, Elsevier Computer Networks Journal, IEEE Trans. on Networking, and IEEE Trans. on Wireless Communications. He co-directs the operations of Colosseum RF/network emulator, as well as the Platforms for Advanced Wireless Research project office. Prof. Chowdhury has served in several leadership roles, including Chair of the IEEE Technical Committee on Simulation, and as Technical Program Chair for IEEE INFOCOM 2021, IEEE CCNC 2021, IEEE  DySPAN 2021, and ACM MobiHoc 2022. His research interests are in large-scale experimentation, applied machine learning for wireless communications and networks, networked robotics, and self-powered Internet of Things.