Sergio Fortes

Data-Driven Adaptive Resource Allocation for Reliable Low-Latency Uplink Communications in Rural Cellular 5G Multi-Connectivity

Carlos S. Alvarez-Merino, Alejandro Ramírez-Arroyo, Rasmus Suhr Mogensen, Morten V. Pedersen et autres

Reliable low-latency communication is a key requirement for mission-critical and mobile autonomous systems, including teleoperation, autonomous navigation, and real-time uplink-dominant telemetry applications. While commercial 5G networks often provide adequate downlink performance, uplink performance in rural deployments may be constrained by radio-resource limitations …

Studying the Role of Synthetic Data for Machine Learning-based Wireless Networks Traffic Forecasting

José Pulido, Francesc Wilhelmi, Sergio Fortes, Alfonso Fernandez-Durán et autres

Synthetic data generation is an appealing tool for augmenting and enriching datasets, playing a crucial role in advancing artificial intelligence (AI) and machine learning (ML). Not only does synthetic data help build robust AI/ML datasets cost-effectively, but it also offers privacy-friendly solutions …

AI-Driven Optimization of Virtual Network Function Allocation in 6G Non-Terrestrial Networks

Francisco Muro, Eduardo Ruiz Baena, Tomaso de Cola, Sergio Fortes et autres

The integration of 6G technologies into Non-Terrestrial Networks (NTNs) presents significant challenges, particularly due to the limited onboard capacities of space-based platforms and their dynamic nature. By leveraging the virtualized 6G O-RAN paradigm, satellites can operate 6G software stacks on Software-Defined Radios …

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Quantum-Based Intelligence for Cellular Network Management: Use Cases, Challenges, and O-RAN Integration

Sergio Fortes, Javier Villegas, Fatma Chaouech, António Pereira et autres

As cellular networks evolve towards 5G and beyond, the increasing complexity demands advanced approaches for efficient management and network intelligence. While classical machine learning (ML) plays a vital role in network planning, optimization and resilience, it faces limitations in handling largescale data …

KPI Synthetic Estimation for Handling Missing Metrics and Updating Cellular Datasets

Juan Cantizani-Estepa, Javier Villegas, Sergio Fortes, Raúl Martín Cuerdo et autres

With the deployment of Fifth Generation (5G) cellular networks, the development and application of Artificial Intelligence (AI) and Machine Learning (ML) techniques has been expanding continuously. Such techniques enhance the reliability, efficiency, capacity, and self-healing capabilities of cellular networks, which require the …

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Experimental Evaluation of Multi-Connectivity Strategies for Reliable Low-Latency Uplink Communications in Rural 5G Networks

Carlos S. Alvarez-Merino, Alejandro Ramírez-Arroyo, Rasmus Suhr Mogensen, Morten V. Pedersen et autres

Reliable low-latency communication is a key requirement for mission-critical and mobile autonomous systems, including teleoperation, autonomous navigation, and real-time uplink-dominant telemetry applications. While commercial 5G networks often provide adequate downlink performance, uplink performance in rural deployments may be constrained by radio-resource limitations …

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Enabling Cloud Robotics in Coverage-Denied Environments: 5G Network-in-a-Box Use Case for SAR Operations With Quadruped Robots

Pablo Vera-Soto, Sergio Fortes, Juan Bravo-Arrabal, J. J. Fernández-Lozano et autres

The Cloud Robotics paradigm is being increasingly implemented in industrial environments and emergency scenarios for reconnaissance and Search And Rescue (SAR) missions, primarily through 5G connectivity. However, the diversity of these scenarios affects the quality of communications. Nevertheless, little literature analyzes the …

An Integrated Framework for Automated Validation and Verification of Avionics Networks

Pablo Vera-Soto, Javier Villegas, Jos´E Pulido, Vicente Esca˜No et autres

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Reinforcement Learning for Channel Allocation: Digital Twin-Based Optimization in Real Large-Scale Wi-Fi Networks

José Pulido, Sergio Fortes, Alfonso Fernandez-Durán, Raquel Barco

Wi-Fi networks, which are based on the IEEE 802.11 standard, are among the most widely used wireless networks worldwide. In recent years, new standards have been introduced that offer a range of benefits to users. However, achieving full potential for these sophisticated …

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Towards KQI/ML-based management: Service-based network slice configuration for next-generation networks

O. S. Peñaherrera-Pulla, Carlos Baena, Hao Qiang Luo-Chen, Sergio Fortes et autres

Next-generation networks, such as Beyond-5G (B5G) and 6G, are expected to support a wide range of services with highly diverse and dynamic requirements. Traditional network management methods, which focus primarily on network-level configurations, are insufficient to handle the complexity and variability of …

Energy-Aware CPU Orchestration in O-RAN: A dApp-Driven Lightweight Approach

Francisco Martos Crespo, Javier Villegas, Carlos Baena, Eduardo Ruiz Baena et autres

The transition toward softwarized Radio Access Networks (RANs), driven by the Open RAN (O-RAN) paradigm, enables flexible, vendor-neutral deployments through disaggregation and virtualization of base station functions. However, this shift introduces new challenges in managing CPU resources efficiently under strict real-time constraints. …

Efficient Resource Allocation for NextG O-RAN VNFs Based on Systematic Characterization

Haoxin Sun, Mattia Lecci, Javier Rivas, Germán Corrales Madueño et autres

The deployment of Virtualized Network Functions (VNFs) in Open Radio Access Network (O-RAN) architectures for beyond 5G (b5G) and 6G networks presents a fundamental challenge in resource dimensioning. Network operators must accurately provision computational, memory and network resources to ensure service reliability …

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