activity
20242026
collaborators

10 papers

eess.SY2026

Bridging Earth and Space: A Survey on HAPS for Non-Terrestrial Networks

G. Svistunov, A. Akhtarshenas, D. López-Pérez +3

HAPS are emerging as key enablers in the evolution of 6G wireless networks, bridging terrestrial and non-terrestrial infrastructures. Operating in the stratosphere, HAPS can provid…

cs.LG2025

A Multi-Task Foundation Model for Wireless Channel Representation Using Contrastive and Masked Autoencoder Learning

Berkay Guler, Giovanni Geraci, Hamid Jafarkhani

Current applications of self-supervised learning to wireless channel representation often borrow paradigms developed for text and image processing, without fully addressing the uni…

cs.NI2025

Quantum Computing for Large-scale Network Optimization: Opportunities and Challenges

Sebastian Macaluso, Giovanni Geraci, Elías F. Combarro +4

The complexity of large-scale 6G-and-beyond networks demands innovative approaches for multi-objective optimization over vast search spaces, a task often intractable. Quantum compu…

cs.IT2025

Data-Driven Cellular Mobility Management via Bayesian Optimization and Reinforcement Learning

Mohamed Benzaghta, Sahar Ammar, David López-Pérez +2

Mobility management in cellular networks faces increasing complexity due to network densification and heterogeneous user mobility characteristics. Traditional handover (HO) mechani…

cs.IT2025

Cellular Network Design for UAV Corridors via Data-driven High-dimensional Bayesian Optimization

Mohamed Benzaghta, Giovanni Geraci, David López-Pérez +1

We address the challenge of designing cellular networks for uncrewed aerial vehicles (UAVs) corridors through a novel data-driven approach. We assess multiple state-of-the-art high…

cs.AI2025

Optimizing UAV Aerial Base Station Flights Using DRL-based Proximal Policy Optimization

Mario Rico Ibanez, Azim Akhtarshenas, David Lopez-Perez +1

Unmanned aerial vehicle (UAV)-based base stations offer a promising solution in emergencies where the rapid deployment of cutting-edge networks is crucial for maximizing life-savin…