59 citations · 482 across the 57 of their papers we have counts for
9 papers · 1 filter
SEM-O-RAN: Semantic and Flexible O-RAN Slicing for NextG Edge-Assisted Mobile Systems
Corrado Puligheddu, Jonathan Ashdown, Carla Fabiana Chiasserini +1
5G and beyond cellular networks (NextG) will support the continuous execution of resource-expensive edge-assisted deep learning (DL) tasks. To this end, Radio Access Network (RAN)…
Toward Integrated Sensing and Communications in IEEE 802.11bf Wi-Fi Networks
Francesca Meneghello, Cheng Chen, Carlos Cordeiro +1
As Wi-Fi becomes ubiquitous in public and private spaces, it becomes natural to leverage its intrinsic ability to sense the surrounding environment to implement groundbreaking wire…
Terahertz Communications Can Work in Rain and Snow: Impact of Adverse Weather Conditions on Channels at 140 GHz
Priyangshu Sen, Jacob Hall, Michele Polese +5
Next-generation wireless networks will leverage the spectrum above 100 GHz to enable ultra-high data rate communications over multi-GHz-wide bandwidths. The propagation environment…
Accurate and Efficient Modeling of 802.15.4 Unslotted CSMA/CA through Event Chains Computation
Domenico De Guglielmo, Francesco Restuccia, Giuseppe Anastasi +2
Many analytical models have been proposed for evaluating the performance of event-driven 802.15.4 Wireless Sensor Networks (WSNs), in Non-Beacon Enabled (NBE) mode. However, existi…
DeepCSI: Rethinking Wi-Fi Radio Fingerprinting Through MU-MIMO CSI Feedback Deep Learning
Francesca Meneghello, Michele Rossi, Francesco Restuccia
We present DeepCSI, a novel approach to Wi-Fi radio fingerprinting (RFP) which leverages standard-compliant beamforming feedback matrices to authenticate MU-MIMO Wi-Fi devices on t…
ChARM: NextG Spectrum Sharing Through Data-Driven Real-Time O-RAN Dynamic Control
Luca Baldesi, Francesco Restuccia, Tommaso Melodia
Today's radio access networks (RANs) are monolithic entities which often operate statically on a given set of parameters for the entirety of their operations. To implement realisti…