Nuria Gonzalez-Prelcic

Associate Professor

North Carolina State University

United States

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Dr. Nuria Gonzalez-Prelcic is an Associate Professor at North Carolina State University, USA. Her research focuses on advanced signal processing, channel estimation, and integrated sensing and communications, particularly in the context of 6G and beyond. Recent publications include innovative solutions for mmWave vehicular systems and hybrid models for multi-functional beamforming.

Articles (19)

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2025

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2020

Collaborators (9)

Pu Wang

Mitsubishi Electric Research Laboratories

UNITED STATES

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Sahan Damith Liyanaarachchi

University of Tampere

FINLAND

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Jordi Borras

Assistant Professor

Universitat Politècnica de Catalunya

SPAIN

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Taneli Riihonen

Associate Professor

University of Tampere

FINLAND

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Mikko Heino

Academy Research Fellow at Tampere University

University of Tampere

FINLAND

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Carlos Baquero Barneto

University of Tampere

FINLAND

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Henk Wymeersch

Professor at Chalmers University of Technology

Chalmers University of Technology

SWEDEN

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Nitin Jonathan Myers

Assistant Professor (tenure track)

Delft University of Technology

NETHERLANDS

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Roberto Lopez-Valcarce

Associate Professor

Universidade de Vigo

SPAIN

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Nuria Gonzalez-Prelcic

Research Interests

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About

Articles (19)

On the Solution to a Class of Multi-Functional Beamforming Problems

Six Integration Avenues for ISAC in 6G and Beyond

A Hybrid Model/Data-Driven Solution to Channel, Position and Orientation Tracking in mmWave Vehicular Systems

The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications

Special Issue on Signal Processing for the Integrated Sensing and Communication Revolution

RIS-Aided Joint Channel Estimation and Localization at mmWave Under Hardware Impairments: A Dictionary Learning-Based Approach

Multicarrier ISAC: Advances in waveform design, signal processing, and learning under nonidealities

Editorial Introduction to the Special Issue on Learning-Based Signal Processing for Integrated Sensing and Communications

Deep Learning-Based Link Configuration for Radar-Aided Multiuser mmWave Vehicle-to-Infrastructure Communication

A Novel Approach for Unit-Modulus Least-Squares Optimization Problems

Hybrid mmWave MIMO Systems under Hardware Impairments and Beam Squint: Channel Model and Dictionary Learning-aided Configuration

Beamformer Design and Optimization for Joint Communication and Full-Duplex Sensing at mm-Waves

Hybrid Beamforming Designs for Frequency-Selective mmWave MIMO Systems With Per-RF Chain or Per-Antenna Power Constraints

Site-Specific Online Compressive Beam Codebook Learning in mmWave Vehicular Communication

Wideband Channel Tracking and Hybrid Precoding for mmWave MIMO Systems

Bayesian Predictive Beamforming for Vehicular Networks: A Low-Overhead Joint Radar-Communication Approach

A Hybrid Beamforming Design for Massive MIMO LEO Satellite Communications

Passive Radar at the Roadside Unit to Configure Millimeter Wave Vehicle-to-Infrastructure Links

Dictionary Learning for Channel Estimation in Hybrid Frequency-Selective mmWave MIMO Systems

Collaborators (9)

Pu Wang

Sahan Damith Liyanaarachchi

Jordi Borras

Taneli Riihonen

Mikko Heino

Carlos Baquero Barneto

Henk Wymeersch

Nitin Jonathan Myers

Roberto Lopez-Valcarce

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