6G-SMART Timeline

IEEE IJCNN 2025

Recently, the University of Jaén had the opportunity to present a research article at the 2025 International Joint Conference on Neural Networks (IJCNN 2025), hosted at the Pontifical Gregorian University, in the city of Rome, Italy. This event brings together the brightest minds in neural networks and artificial intelligence, offering a platform for sharing ideas and fostering collaborations.

The paper “Digital Twin-Based Deep Q-Learning Strategy for Smart Handover Optimization in 5G/6G Networks”, presents a digital twin-based Deep Q-Learning (DQL) strategy to optimize handover processes and resource management in these networks. It is proposed to consider digital twins to support the implementation of real-time network conditions where DQL agents are trained to improve quality of service (QoS) parameters related to throughput. The suggested approach, deployed with the ns-3 mmWave module and ns3-ai framework, shows relevant benefits, including reduced handovers. Moreover, the consideration of digital twins allows adaptive learning and scalability, allowing networks to respond more effectively to dynamic user behavior and environmental modifications. These results underline the potential of combining DQL and digital twins as an efficient solution for smart handover management, and thus, for sustainable and efficient communication in 5G/6G networks.

📃 The full paper can be accessed: Here!

📆 Stay tuned for updates as we keep looking forward to future collaborations and continued innovation in wireless communications!

IEEE WCNC 2025

Recently, Celfinet a Cyient Company had the opportunity to present a research article at the IEEE Wireless Communications and Networking Conference (WCNC 2025), an excellent event where researchers and industry professionals discuss and explore advancements in wireless communication technologies.

The paper "Telco-DPR: A Hybrid Dataset for Evaluating Retrieval Models of 3GPP Technical Specifications," introduces Telco-DPR, an open-access dataset combining text and table formats from curated 3GPP documents. The dataset includes synthetic question-passage pairs designed to evaluate retrieval performance in telecom-focused question-answering systems. Our research showed significant improvements over traditional Retriever-Augmented Generation (RAG) methods. Specifically, our proposed system, integrating Dense Hierarchical Retrieval (DHR) with GPT-4, achieved a 14% improvement in answer accuracy compared to existing benchmarks.

📃 The full paper can be accessed: Here!

🔎 The Telco-DPR dataset was made openly available to encourage further research and development and can be accessed: Here!

Special thanks to the co-authors Pedro Vieira and António Rodrigues, and especially Thaína Saraiva as the first author, to the 6G-SMART project partners, Instituto de Telecomunicações, and ISEL - Instituto Superior De Engenharia De Lisboa for their valuable support.

📆 Stay tuned for updates as we keep looking forward to future collaborations and continued innovation in wireless communications!

6G-SMART Kick-off

The 6G-SMART project has officially started.