301 citations · 1.9k across the 75 of their papers we have counts for
14 papers · 1 filter
DeepBeam: Deep Waveform Learning for Coordination-Free Beam Management in mmWave Networks
Michele Polese, Francesco Restuccia, Tommaso Melodia
Highly directional millimeter wave (mmWave) radios need to perform beam management to establish and maintain reliable links. To do so, existing solutions mostly rely on explicit co…
Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks
Leonardo Bonati, Salvatore D'Oro, Michele Polese +2
Next Generation (NextG) cellular networks will be natively cloud-based and built upon programmable, virtualized, and disaggregated architectures. The separation of control function…
An Experimental mmWave Channel Model for UAV-to-UAV Communications
Michele Polese, Lorenzo Bertizzolo, Leonardo Bonati +2
Unmanned Aerial Vehicle (UAV) networks can provide a resilient communication infrastructure to enhance terrestrial networks in case of traffic spikes or disaster scenarios. However…
SwarmControl: An Automated Distributed Control Framework for Self-Optimizing Drone Networks
Lorenzo Bertizzolo, Salvatore D'oro, Ludovico Ferranti +5
Networks of Unmanned Aerial Vehicles (UAVs), composed of hundreds, possibly thousands of highly mobile and wirelessly connected flying drones will play a vital role in future Inter…
DeepFIR: Addressing the Wireless Channel Action in Physical-Layer Deep Learning
Francesco Restuccia, Salvatore D'Oro, Amani Al-Shawabka +3
Deep learning can be used to classify waveform characteristics (e.g., modulation) with accuracy levels that are hardly attainable with traditional techniques. Recent research has d…
Hacking the Waveform: Generalized Wireless Adversarial Deep Learning
Francesco Restuccia, Salvatore D'Oro, Amani Al-Shawabka +4
This paper advances the state of the art by proposing the first comprehensive analysis and experimental evaluation of adversarial learning attacks to wireless deep learning systems…
PolymoRF: Polymorphic Wireless Receivers Through Physical-Layer Deep Learning
Francesco Restuccia, Tommaso Melodia
Today's wireless technologies are largely based on inflexible designs, which makes them inefficient and prone to a variety of wireless attacks. To address this key issue, wireless…
Sl-EDGE: Network Slicing at the Edge
Salvatore D'Oro, Leonardo Bonati, Francesco Restuccia +3
Network slicing of multi-access edge computing (MEC) resources is expected to be a pivotal technology to the success of 5G networks and beyond. The key challenge that sets MEC slic…
Open, Programmable, and Virtualized 5G Networks: State-of-the-Art and the Road Ahead
Leonardo Bonati, Michele Polese, Salvatore D'Oro +2
Fifth generation (5G) cellular networks will serve a wide variety of heterogeneous use cases, including mobile broadband users, ultra-low latency services and massively dense conne…
Toward End-to-End, Full-Stack 6G Terahertz Networks
Michele Polese, Josep Jornet, Tommaso Melodia +1
Recent evolutions in semiconductors have brought the terahertz band in the spotlight as an enabler for terabit-per-second communications in 6G networks. Most of the research so far…
Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning with Deep Unfolding
Anu Jagannath, Jithin Jagannath, Tommaso Melodia
The year 2019 witnessed the rollout of the 5G standard, which promises to offer significant data rate improvement over 4G. While 5G is still in its infancy, there has been an incre…
Deep Learning at the Physical Layer: System Challenges and Applications to 5G and Beyond
Francesco Restuccia, Tommaso Melodia
The unprecedented requirements of the Internet of Things (IoT) have made fine-grained optimization of spectrum resources an urgent necessity. Thus, designing techniques able to ext…
CellOS: Zero-touch Softwarized Open Cellular Networks
Leonardo Bonati, Salvatore D'Oro, Lorenzo Bertizzolo +4
Current cellular networks rely on closed and inflexible infrastructure tightly controlled by a handful of vendors. Their configuration requires vendor support and lengthy manual op…
CoBeam: Beamforming-based Spectrum Sharing With Zero Cross-Technology Signaling for 5G Wireless Networks
Lorenzo Bertizzolo, Emrecan Demirors, Zhangyu Guan +1
This article studies an essential yet challenging problem in 5G wireless networks: \emph{Is it possible to enable spectrally-efficient spectrum sharing for heterogeneous wireless n…