activity
20232026
most citedOpportunities and Challenges for Virtual Reality Streaming over Millimeter-Wave: An Experimental Analysis

12 citations · 23 across the 9 of their papers we have counts for

collaborators

9 papers

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★ 6 cited

SymbXRL: Symbolic Explainable Deep Reinforcement Learning for Mobile Networks

Abhishek Duttagupta, MohammadErfan Jabbari, Claudio Fiandrino +2

The operation of future 6th-generation (6G) mobile networks will increasingly rely on the ability of deep reinforcement learning (DRL) to optimize network decisions in real-time. D…

cs.NI2026

Spectrum & RAN Sharing: A Measurement-based Case Study of Commercial 5G Networks in Spain

Rostand A. K. Fezeu, Lilian C. Freitas, Eman Ramadan +4

Radio Access Network (RAN) sharing, which often also includes spectrum sharing, is a strategic cooperative agreement among two or more mobile operators, where one operator may use…

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★ 12 cited

Opportunities and Challenges for Virtual Reality Streaming over Millimeter-Wave: An Experimental Analysis

Jakob Struye, Hemanth Kumar Ravuri, Hany Assasa +5

Achieving extremely high-quality and truly immersive interactive Virtual Reality (VR) is expected to require a wireless link to the cloud, providing multi-gigabit throughput and ex…

cs.NI2024★ 4 cited

Twinning Commercial Network Traces on Experimental Open RAN Platforms

Leonardo Bonati, Ravis Shirkhani, Claudio Fiandrino +4

While the availability of large datasets has been instrumental to advance fields like computer vision and natural language processing, this has not been the case in mobile networki…

cs.NI2023

waveSLAM: Empowering Accurate Indoor Mapping Using Off-the-Shelf Millimeter-wave Self-sensing

Pablo Picazo, Milan Groshev, Alejandro Blanco +3

This paper presents the design, implementation and evaluation of waveSLAM, a low-cost mobile robot system that uses the millimetre wave (mmWave) communication devices to enhance th…

cs.NI2023

EXPLORA: AI/ML EXPLainability for the Open RAN

Claudio Fiandrino, Leonardo Bonati, Salvatore D'Oro +3

The Open Radio Access Network (RAN) paradigm is transforming cellular networks into a system of disaggregated, virtualized, and software-based components. These self-optimize the n…

cs.NI2023★ 1 cited

Mid-Band 5G: A Measurement Study in Europe and US

Rostand A. K. Fezeu, Jason Carpenter, Claudio Fiandrino +5

Fifth Generation (5G) mobile networks mark a significant shift from previous generations of networks. By introducing a flexible design, 5G networks support highly diverse applicati…