activity
20162026
most citedA Tutorial on Beam Management for 3GPP NR at mmWave Frequencies

671 citations · 3.8k across the 116 of their papers we have counts for

collaborators

120 papers

cs.NI2026

Coordinated Spectrum Coexistence Across Heterogeneous Commercial and Federal Services

Minh Dat Nguyen, Paolo Testolina, Pedram Johari +2

Future wireless networks are expected to support the coexistence of cellular communications, radio frequency (RF) sensing, radionavigation, and radiolocation radar-among others-ove…

eess.SY2026

Spectrum Sharing Across Terrestrial and Non-Terrestrial Services in the FR3 Upper Midband

Paolo Testolina, Ergest Beshaj, Michele Polese +1

The frequency bands between 7 and 24 GHz, also known as upper midband or Frequency Range (FR) 3, are being considered as an enabler of 6th Generation (6G) mobile networks. This por…

cs.NI2026

Satellite-Terrestrial Spectrum Sharing in FR3 through QoS-Aware Power Control and Spatial Nulling

Maria Tsampazi, Paolo Testolina, Michele Polese +1

Frequency Range 3 (FR3), encompassing frequencies between 7.125 and 24.25 GHz, is an emerging frequency band for 6th generation (6G) applications. The upper mid-band, as it is freq…

cs.NI2026

Predicting Conflict Impact on Performance in O-RAN

Pietro Brach del Prever, Niloofar Mohamadi, Salvatore D'Oro +7

The O-RAN Alliance promotes the integration of intelligent autonomous agents to control the Radio Access Network (RAN). This improves flexibility, performance, and observability in…

cs.NI2026

A Techno-Economic Framework for Cost Modeling and Revenue Opportunities in Open and Programmable AI-RAN

Gabriele Gemmi, Michele Polese, Tommaso Melodia

The large-scale deployment of 5G networks has not delivered the expected return on investment for mobile network operators, raising concerns about the economic viability of future…

eess.SP2026

From High-Level Requirements to KPIs: Conformal Signal Temporal Logic Learning for Wireless Communications

Jiechen Chen, Michele Polese, Osvaldo Simeone

Softwarized radio access networks (RANs), such as those based on the Open RAN (O-RAN) architecture, generate rich streams of key performance indicators (KPIs) that can be leveraged…

cs.NI2026

TENORAN: Automating Fine-grained Energy Efficiency Profiling in Open RAN Systems

Ravis Shirkhani, Stefano Maxenti, Leonardo Bonati +7

The transition to disaggregated and interoperable Open Radio Access Network (RAN) architectures and the introduction of RAN Intelligent Controllers (RICs) in O-RAN creates new reso…

cs.NI2026

xDevSM: An Open-Source Framework for Portable, AI-Ready xApps Across Heterogeneous O-RAN Deployments

Angelo Feraudo, Stefano Maxenti, Andrea Lacava +4

Openness and programmability in the O-RAN architecture enable closed-loop control of the Radio Access Network (RAN). Artificial Intelligence (AI)-driven xApps, in the near-real-tim…

eess.SP2026

On the Spatial Consistency of Sub-Terahertz Channel Characteristics for Beyond-6G Systems

Hossein Amininasab, Huda Farooqui, Dmitri Moltchanov +4

Ray tracing is a versatile approach for precise sub-terahertz (sub-THz, 100-300 GHz) channel modeling when designing new mechanisms for beyond-6G cellular systems. Theoretically, w…

cs.NI2026

SIA: Symbolic Interpretability for Anticipatory Deep Reinforcement Learning in Network Control

MohammadErfan Jabbari, Abhishek Duttagupta, Claudio Fiandrino +5

Deep reinforcement learning (DRL) promises adaptive control for future mobile networks but conventional agents remain reactive: they act on past and current measurements and cannot…

cs.NI2026

MANATEE: A DevOps Platform for xApp Lifecycle Management and Testing in Open RAN

Sofia Montebugnoli, Leonardo Bonati, Andrea Sabbioni +5

The shift to disaggregated 5G architectures introduces unprecedented flexibility but also significant complexity in Beyond 5G Radio Access Networks (RANs). Open RAN enables program…

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

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…

cs.NI2025

On AI Verification in Open RAN

Rahul Soundrarajan, Claudio Fiandrino, Michele Polese +3

Open RAN introduces a flexible, cloud-based architecture for the Radio Access Network (RAN), enabling Artificial Intelligence (AI)/Machine Learning (ML)-driven automation across he…

cs.NI2025

Pointing-Error-Induced Fading in an Open-Loop THz Uplink with Hardware Impairments

P. Brach del Prever, P. Testolina, A. Masihi +4

We analyze the open-loop mechanical tracking performance of a sub-Terahertz (sub-THz) and Terahertz (THz) uplink communication system. These high-frequency bands enable multi-gigab…

cs.NI2025

Joint Routing, Resource Allocation, and Energy Optimization for Integrated Access and Backhaul with Open RAN

Reshma Prasad, Maxime Elkael, Gabriele Gemmi +6

As networks evolve towards 6G, Mobile Network Operators (MNOs) must accommodate diverse requirements and at the same time manage rising energy consumption. Integrated Access and Ba…

cs.NI2025

TailO-RAN: O-RAN Control on Scheduler Parameters to Tailor RAN Performance

Nicolo Longhi, Salvatore D'Oro, Leonardo Bonati +3

The traditional black-box and monolithic approach to Radio Access Networks (RANs) has heavily limited flexibility and innovation. The Open RAN paradigm, and the architecture propos…

cs.NI2025

Enabling Site-Specific Cellular Network Simulation Through Ray-Tracing-Driven ns-3

Tanguy Ropitault, Matteo Bordin, Paolo Testolina +4

Evaluating cellular systems, from 5G New Radio (NR) and 5G-Advanced to 6G, is challenging because the performance emerges from the tight coupling of propagation, beam management, s…

cs.AI2025

AgentRAN: An Agentic AI Architecture for Autonomous Control of Open 6G Networks

Maxime Elkael, Salvatore D'Oro, Leonardo Bonati +4

Despite the programmable architecture of Open RAN, today's deployments still rely heavily on static control and manual operations. To move beyond this limitation, we introduce Agen…

cs.NI2025

InterfO-RAN: Real-Time In-band Cellular Uplink Interference Detection with GPU-Accelerated dApps

Neagin Neasamoni Santhi, Davide Villa, Michele Polese +1

Ultra-dense fifth generation (5G) and beyond networks leverage spectrum sharing and frequency reuse to enhance throughput, but face unpredictable in-band uplink (UL) interference c…

cs.NI2025

Beyond Connectivity: An Open Architecture for AI-RAN Convergence in 6G

Michele Polese, Niloofar Mohamadi, Salvatore D'Oro +2

Data-intensive Artificial Intelligence (AI) applications at the network edge demand a fundamental shift in Radio Access Network (RAN) design, from merely consuming AI for network o…

cs.NI2025

Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence

Eduardo Baena, Paolo Testolina, Michele Polese +5

Lunar surface operations impose stringent requirements on wireless communication systems, including autonomy, robustness to disruption, and the ability to adapt to environmental an…

cs.NI2025

ALLSTaR: Automated LLM-Driven Scheduler Generation and Testing for Intent-Based RAN

Maxime Elkael, Michele Polese, Reshma Prasad +2

The evolution toward open, programmable O-RAN and AI-RAN 6G networks creates unprecedented opportunities for Intent-Based Networking (IBN) to dynamically optimize RAN[...]. However…

cs.NI2025★ 1 cited

AutoRAN: Automated and Zero-Touch Open RAN Systems

Stefano Maxenti, Ravis Shirkhani, Maxime Elkael +4

[...] This paper presents AutoRAN, an automated, intent-driven framework for zero-touch provisioning of open, programmable cellular networks. Leveraging cloud-native principles, Au…