5 papers
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…
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…
Data-Driven Design of 3GPP Handover Parameters with Bayesian Optimization and Transfer Learning
Mohamed Benzaghta, Sahar Ammar, David López-Pérez +2
Mobility management in dense cellular networks is challenging due to varying user speeds and deployment conditions. Traditional 3GPP handover (HO) schemes, relying on fixed A3-offs…
Data-driven Optimization and Transfer Learning for Cellular Network Antenna Configurations
Mohamed Benzaghta, Giovanni Geraci, David López-Pérez +1
We propose a data-driven approach for large-scale cellular network optimization, using a production cellular network in London as a case study and employing Sionna ray tracing for…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…