activity
20242026
most citedEnabling Deep Reinforcement Learning Research for Energy Saving in Open RAN

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.NI20262 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

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

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…