5 papers
Hardware-in-the-Loop Phase-Aware CNN for Real-Time 5G Channel Estimation
Javad Zolfaghari-Bengar, Rakibul Rony, Elisa Gomez-de-Lope +3
This demo presents real-time AI-based uplink channel-estimation inference using data collected from a hardware-in-the-loop 5G platform. The data-collection setup integrates commerc…
Phase-Aware CNN for Real-Time 5G/6G Channel Estimation with Hardware-in-the-loop Validation
Javad Zolfaghari-Bengar, Rakibul Rony, Elisa Gomez-de-Lope +3
In 5G/6G wireless systems, accurate and timely channel estimation is critical to ensure reliable communication under complex, fast-changing radio conditions. This work focuses on p…
CSI-4CAST: A Hybrid Deep Learning Model for CSI Prediction with Comprehensive Robustness and Generalization Testing
Sikai Cheng, Reza Zandehshahvar, Haoruo Zhao +4
Channel state information (CSI) prediction is a promising strategy for ensuring reliable and efficient operation of massive multiple-input multiple-output (mMIMO) systems by provid…
Aging-Resistant Wideband Precoding in 5G and Beyond Using 3D Convolutional Neural Networks
Alejandro Villena-Rodriguez, Francisco J. MartÃn-Vega, Gerardo Gómez +2
To meet the ever-increasing demand for higher data rates, 5G and 6G technologies are shifting transceivers to higher carrier frequencies, to support wider bandwidths and more anten…
AI-Assisted Dynamic Port and Waveform Switching for Enhancing UL Coverage in 5G NR
Alejandro Villena-RodrÃguez, Gerardo Gómez, Mari Carmen Aguayo-Torres +4
The uplink of 5G networks allows selecting the transmit waveform between cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) and discrete Fourier transform spread OF…