Nuria González-Prelcic

Biography

Dr. González Prelcic received her Ph.D. in Electrical Engineering in 2000 from the University of Vigo, Spain. She joined the faculty at NC State as an Associate Professor in 2020. She was previously an Associate Professor in the Signal Theory and Communications Department at the University of Vigo, Spain, and a Senior Research Scientist at the University of Texas at Austin (2018-2020). She was also the founding director of the Atlantic Research Center for Information and Communication Technologies (atlanTTic) at the University of Vigo (2008-2017). She is an Editor for IEEE Transactions on Wireless Communications. She is an elected member of the IEEE Sensor Array and Multichannel Technical Committee.

Her main research interests include signal processing theory and signal processing and machine learning for wireless communications: filter banks, compressive sampling and estimation, multicarrier modulation, massive MIMO, MIMO processing for millimeter-wave communication and sensing, including vehicle-to-everything (V2X), air-to-everything (A2X) and satellite MIMO communication. She is also interested in joint positioning and communication, joint sensing and communication, radar signal processing, radar and communications co-existence, multi-vehicle sensor fusion and autonomous navigation. She has published more than 80 papers in the topic of signal processing for millimeter-wave communications, including a highly cited tutorial published in the IEEE Journal of Selected Topics in Signal Processing.

Education

• Ph.D. 2000
  Electrical Engineering
  University of Vigo, Spain

Recent Publications

• A Novel Approach for Unit-Modulus Least-Squares Optimization Problems (2023)
• Deep Learning-Based Link Configuration for Radar-Aided Multiuser mmWave Vehicle-to-Infrastructure Communication (2023)
• Hybrid mmWave MIMO Systems Under Hardware Impairments and Beam Squint: Channel Model and Dictionary Learning-Aided Configuration (2023)
• Beam Codebook Design for Joint Initial Access and Localization in mmWave Networks (2022)
• Beamformer Design and Optimization for Joint Communication and Full-Duplex Sensing at mm-Waves (2022)
• Hybrid Beamforming Designs for Frequency-Selective mmWave MIMO Systems With Per-RF Chain or Per-Antenna Power Constraints (2022)
• Bayesian Predictive Beamforming for Vehicular Networks: A Low-Overhead Joint Radar-Communication Approach (2021)
• Deep Transfer Learning for Site-Specific Channel Estimation in Low-Resolution mmWave MIMO (2021)
• Site-Specific Online Compressive Beam Codebook Learning in mmWave Vehicular Communication (2021)
• Wideband Channel Tracking and Hybrid Precoding for mmWave MIMO Systems (2021)