21 citations · 35 across the 10 of their papers we have counts for
10 papers
Programmable and GPU-Accelerated Edge Inference for Real-Time ISAC on NVIDIA Aerial Testbed
Davide Villa, Mauro Belgiovine, Nicholas Hedberg +3
The transition of cellular networks to (i) software-based systems on commodity hardware and (ii) platforms for services beyond connectivity introduces critical system-level challen…
ATLAS: AI-Native Receiver Test-and-Measurement by Leveraging AI-Guided Search
Mauro Belgiovine, Suyash Pradhan, Johannes Lange +2
Industry adoption of Artificial Intelligence (AI)-native wireless receivers, or even modular, Machine Learning (ML)-aided wireless signal processing blocks, has been slow. The main…
T-PRIME: Transformer-based Protocol Identification for Machine-learning at the Edge
Mauro Belgiovine, Joshua Groen, Miquel Sirera +5
Spectrum sharing allows different protocols of the same standard (e.g., 802.11 family) or different standards (e.g., LTE and DVB) to coexist in overlapping frequency bands. As this…
From Classification to Optimization: Slicing and Resource Management with TRACTOR
Joshua Groen, Zixian Yang, Divyadharshini Muruganandham +3
5G and beyond networks promise advancements in bandwidth, latency, and connectivity. The Open Radio Access Network (O-RAN) framework enhances flexibility through network slicing an…
Neural Network-based OFDM Receiver for Resource Constrained IoT Devices
Nasim Soltani, Hai Cheng, Mauro Belgiovine +10
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the…
Going Beyond RF: How AI-enabled Multimodal Beamforming will Shape the NextG Standard
Debashri Roy, Batool Salehi, Stella Banou +7
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G wireless standard promises autonomous network behavior and ultra-low-latency reconfiguratio…
Machine Learning on Camera Images for Fast mmWave Beamforming
Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez +3
Perfect alignment in chosen beam sectors at both transmit- and receive-nodes is required for beamforming in mmWave bands. Current 802.11ad WiFi and emerging 5G cellular standards s…
DeepRadioID: Real-Time Channel-Resilient Optimization of Deep Learning-based Radio Fingerprinting Algorithms
Francesco Restuccia, Salvatore D'Oro, Amani Al-Shawabka +5
Radio fingerprinting provides a reliable and energy-efficient IoT authentication strategy. By mapping inputs onto a very large feature space, deep learning algorithms can be traine…
ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks
Kunal Sankhe, Mauro Belgiovine, Fan Zhou +3
This paper describes the architecture and performance of ORACLE, an approach for detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol, physica…
GPGPU for track finding in High Energy Physics
Lorenzo Rinaldi, Mauro Belgiovine, Riccardo Di Sipio +6
The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become eve…