4 papers
HELENA for 5G NR LEO NTN Channel Estimation: A Comparative Evaluation
Miguel Camelo Botero, Nina Slamnik-Kriještorac, Johann Marquez-Barja
Deep Learning (DL)-based channel estimation has shown high accuracy and low latency in terrestrial 5G NR, but Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) introduce Dopple…
Towards Trustworthy 6G Network Digital Twins: A Framework for Validating Counterfactual What-If Analysis in Edge Computing Resources
Julian Jimenez Agudelo, Paola Soto, Ayat Zaki-Hindi +5
Network Digital Twins (NDTs) enable safe what-if analysis for 6G cloud-edge infrastructures, but adoption is often limited by fragmented workflows from telemetry to validation. We…
LITE: Lightweight Channel Gain Estimation with Reduced X-Haul CSI Signaling in O-RAN
David Goez, Marco Piazzola, Giulia Costa +6
Cell-Free Massive Multiple-Input Multiple-Output (CF-MaMIMO) in Open Radio Access Network (O-RAN) promises high spectral efficiency but is limited by frequent Channel State Informa…
HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attention
Miguel Camelo Botero, Esra Aycan Beyazit, Nina Slamnik-Kriještorac +1
Accurate channel estimation is critical for high-performance Orthogonal Frequency-Division Multiplexing systems such as 5G New Radio, particularly under low signal-to-noise ratio a…