activity
20242026
most citeddApps: Enabling Real-Time AI-Based Open RAN Control

18 citations · 21 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NI2026

StormShield: Fingerprint-Based Detection and Mitigation of RRC Signaling Storms in O-RAN 5G RANs

Noemi Giustini, Andrea Lacava, Leonardo Bonati +4

5G networks provide low-latency, high throughput, and massive connectivity, yet the control plane remains exposed to several security threats. Among the most common and impactful t…

cs.NI2026★ 2 cited

Enabling Deep Reinforcement Learning Research for Energy Saving in Open RAN

Matteo Bordin, Andrea Lacava, Michele Polese +2

The growing performance demands and higher deployment densities of next-generation wireless systems emphasize the importance of adopting strategies to manage the energy efficiency…

cs.NI2025★ 1 cited

LibIQ: Toward Real-Time Spectrum Classification in O-RAN dApps

Filippo Olimpieri, Noemi Giustini, Andrea Lacava +3

The O-RAN architecture is transforming cellular networks by adopting RAN softwarization and disaggregation concepts to enable data-driven monitoring and control of the network. Suc…

cs.NI2025★ 18 cited

dApps: Enabling Real-Time AI-Based Open RAN Control

Andrea Lacava, Leonardo Bonati, Niloofar Mohamadi +7

Open Radio Access Networks (RANs) leverage disaggregated and programmable RAN functions and open interfaces to enable closed-loop, data-driven radio resource management. This is pe…

cs.NI2024

TIMESAFE: Timing Interruption Monitoring and Security Assessment for Fronthaul Environments

Joshua Groen, Simone Di Valerio, Imtiaz Karim +9

5G and beyond cellular systems embrace the disaggregation of Radio Access Network (RAN) components, exemplified by the evolution of the fronthaul (FH) connection between cellular b…

cs.NI2024

TwiNet: Connecting Real World Networks to their Digital Twins Through a Live Bidirectional Link

Clifton Paul Robinson, Andrea Lacava, Pedram Johari +2

The wireless spectrum's increasing complexity poses challenges and opportunities, highlighting the necessity for real-time solutions and robust data processing capabilities. Digita…

cs.NI2024

Design and Evaluation of Deep Reinforcement Learning for Energy Saving in Open RAN

Matteo Bordin, Andrea Lacava, Michele Polese +5

Next-generation wireless systems, already widely deployed, are expected to become even more prevalent in the future, representing challenges in both environmental and economic term…