https://hdl.handle.net/20.500.12008/5205 Incluye artículos, objetos de conferencias, seminarios y jornadas, reportes técnicos, comunicaciones y otros 2026-08-22T05:42:55Z https://hdl.handle.net/20.500.12008/56175 Título: Optimal design of renewable generation mix for green hydrogen production Autor: Accinelli, Elvio; Risso, Claudio; Vignolo, Mario; Nuñez, Facundo Resumen: Green hydrogen is emerging as a key energy vector for the decarbonization of modern energy systems by enabling the storage and transport of renewable energy. It is produced through water electrolysis powered by renewable electricity, either on-site or supplied by a high-renewable grid. Its applications include hard-to-abate industrial sectors (e.g., steel and cement), long-distance transport, and as a feedstock for chemical synthesis, including clean synthetic fuels when combined with CO2 capture. In power systems with high shares of wind and solar generation, green hydrogen also plays a strategic role in managing surplus energy and reducing curtailment. This paper develops a quantitative framework to determine the optimal mix of renewable generation technologies for hydrogen production, incorporating generation variability, grid interactions, and long-term financial evaluation based on Net Present Value. 2026-01-01T00:00:00Z https://hdl.handle.net/20.500.12008/55916 Título: AI learns G-PON : Toward adaptive T-CONT configuration for fixed-mobile convergence Autor: Inglés, Lucas; Anet Neto, Luiz; Rattaro, Claudina; Morvan, Michel; Castro, Alberto; Nuaymi, Loutfi Resumen: We demonstrate the use of a commercial G-PON as an AI-enhanced self-optimizing substrate. We refine the T-CONT configuration with deep reinforcement learning to optimize transmission latency and ensure stable and adaptive performances for fixed-mobile convergent scenarios. 2026-01-01T00:00:00Z https://hdl.handle.net/20.500.12008/55913 Título: Measurements of beamforming performance in commercial 5G deployments Autor: Benedetti, Bruno; Rattaro, Claudina; Rodríguez Díaz, Benigno Resumen: This paper presents field measurements of different beamforming mechanisms using a commercial 5 G network. Beamforming enhances signal quality and capacity through directional transmission, and its effectiveness depends on factors like user position and feedback. We analyze Sounding Reference Signal (SRS)-based and codebook-based beamforming under real-world conditions. Results show SRS-based beamforming excels in mid-cell areas, while codebook-based performs better at the cell edge. 2026-01-01T00:00:00Z https://hdl.handle.net/20.500.12008/55911 Título: Demystifying O-RAN implementations under resource-constrained hardware : an experimental evaluation Autor: Navarro Gutiérrez, Juan; Castro, Alberto; Astudillo, Carlos A.; Rattaro, Claudina Resumen: Open Radio Access Network (O-RAN) has emerged as a disruptive paradigm for mobile networks by disaggregating traditional RAN functions into software-based components interconnected through open and interoperable interfaces. By enabling multi-vendor integration, cloud-native deployments, and programmability via rApps and xApps, O-RAN promises increased flexibility, innovation, and cost efficiency. However, due to the rapid evolution of specifications, software stacks, and experimental platforms, practical knowledge on how to experiment with O-RAN remains fragmented and difficult to access, particularly for laboratories with limited hardware resources. This paper presents a structured theoretical and practical study of the O-RAN ecosystem aimed at lowering the entry barrier to academic and small-scale research. First, we consolidate the architectural foundations of O-RAN, including its main components, interfaces, and control principles. Then, we comparatively evaluate five representative open O-RAN testbeds spanning simulated, hybrid, automated, and flexible emulated deployments, all analyzed from the perspective of reproducibility, deployment complexity, realism, and resource requirements. Rather than providing an exhaustive benchmark of O-RAN performance, the paper offers a reproducible, decision-oriented guide to help researchers select the most appropriate experimentation platform for their needs. Illustrative use cases are implemented on the most promising platforms to validate monitoring, control, and integration capabilities. All configurations and scripts are publicly released to support reproducibility and future experimentation on open and intelligent RAN solutions. 2026-01-01T00:00:00Z