activity
20122026
most citedRician MIMO Channel- and Jamming-Aware Decision Fusion

215 citations · 1.1k across the 21 of their papers we have counts for

collaborators

21 papers

cs.NI2026

Lightweight GenAI for Network Traffic Generation: Fidelity, Augmentation, and Classification

Giampaolo Bovenzi, Domenico Ciuonzo, Jonatan Krolikowski +4

Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited labeled data, strict privacy requiremen…

cs.NI2025★ 17 cited

Mapping the Landscape of Generative AI in Network Monitoring and Management

Giampaolo Bovenzi, Francesco Cerasuolo, Domenico Ciuonzo +5

Generative Artificial Intelligence (GenAI) models such as LLMs, GPTs, and Diffusion Models have recently gained widespread attention from both the research and the industrial commu…

eess.SP2022★ 19 cited

Distributed Detection Fusion in Clustered Sensor Networks over Multiple Access Fading Channels

Sami Aldalahmeh, Domenico Ciuonzo

In this paper, we tackle decision fusion for distributed detection in a randomly-deployed clustered wireless sensor networks (WSNs) operating over a non-ideal multiple access chann…

cs.NI2021★ 14 cited

A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification

Giampaolo Bovenzi, Lixuan Yang, Alessandro Finamore +4

The recent popularity growth of Deep Learning (DL) re-ignited the interest towards traffic classification, with several studies demonstrating the accuracy of DL-based classifiers t…

eess.SP2020

Wideband Collaborative Spectrum Sensing using Massive MIMO Decision Fusion

I. Dey, D. Ciuonzo, P. Salvo Rossi

In this paper, in order to tackle major challenges of spectrum exploration \& allocation in Cognitive Radio (CR) networks, we apply the general framework of Decision Fusion (DF) to…

cs.IT2017★ 65 cited

On Time-Reversal Imaging by Statistical Testing

D. Ciuonzo

This letter is focused on the design and analysis of computational wideband time-reversal imaging algorithms, designed to be adaptive with respect to the noise levels pertaining to…