{"id":12058,"date":"2025-04-03T15:53:25","date_gmt":"2025-04-03T15:53:25","guid":{"rendered":"https:\/\/www.eucnc.eu\/?page_id=12058"},"modified":"2025-05-27T13:04:36","modified_gmt":"2025-05-27T13:04:36","slug":"special-session-19","status":"publish","type":"page","link":"https:\/\/www.eucnc.eu\/programme\/special-sessions\/special-session-19\/","title":{"rendered":"Special Session 19"},"content":{"rendered":"

AURA-6G: Towards an AI-native, service oriented, ubiquitous and verifiable 6G integrated fabric<\/h2>\n

Thursday, 5 June 2025, 16:00 \u2013 17:30, room 0.A<\/h6>\n
Session Chair:<\/h5>\n
    \n
  • Engin Zeydan<\/strong> (Centre Tecnol\u00f2gic de Telecomunicacions de Catalunya (CTTC), ES)<\/li>\n
  • Tomaso De Cola<\/strong> (Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR), DE)<\/li>\n
  • Michael Dieudonne<\/strong> (Keysight Technologies, )<\/li>\n
  • Luis Blanco<\/strong> (Centre Tecnol\u00f2gic de Telecomunicacions de Catalunya (CTTC), ES)<\/li>\n
  • Elli Kartsakli<\/strong> (Barcelona Supercomputing Center (BSC), ES)<\/li>\n<\/ul>\n

    The convergence of terrestrial networks (TN), non-terrestrial networks (NTN) and Non-Public Networks (NPN) is essential for achieving the ambitious goals of 5G and 6G networks. Coupled with AI-driven orchestration, dynamic resource allocation, and semantic communication, these technologies represent the backbone of next-generation connectivity. This workshop aims to explore innovative methodologies for integrating TN, NTN NPN, leveraging AI\/ML, and creating sustainable, scalable 6G architectures. Given the strategic importance of these areas, this workshop offers a platform for researchers, industry leaders, and policymakers to share insights, discuss challenges, and shape the roadmap for 6G advancements. This workshop will be a critical topic for the EuCNC & 6G Summit 2025 due to its direct alignment with the strategic objectives of Europe in maintaining global competitiveness and fostering cutting-edge innovation in integrated networks and AI technologies.<\/p>\n

    Programme<\/h5>\n

    16:00 – 16:20: Keynote: Luis Miguel Contreras Murillo, <\/strong>Transport, IP and Interconnection Networks \/ GCTO Unit \/ Telef\u00f3nica
    \n<\/strong>Title of the talk:
    \nTN-NTN integration, AI-native architectures, and digital twins.<\/p>\n

    16:20 – 16:35: Talk by Tomaso de Cola<\/strong>, DLR, Luis Blanco<\/strong>, CTTC, Cristian J. Vaca-Rubio<\/strong>, CTTC, Marius Caus<\/strong>, CTTC, Fanny Parzysz<\/strong>, Orange Innovation, Laurent Reynaud<\/strong>, Orange Innovation, Daniele Tarchi<\/strong>, CNIT, Roshith Sebastian<\/strong>, DLR, Benjamin Barth<\/strong>, DLR, Swapnil Sadashiv Shinde<\/strong>, CNIT, David Naseh<\/strong>, CNIT<\/p>\n

    Title of the talk:
    \nData-Driven Design of Integrated B5G-NTN Systems: The 5G-STARDUST Perspective
    \nAutomatisation of network operations is a compelling priority for service operators and manufacturers in view of the forthcoming 6G systems design. In this regard, the exploitation of AI-based solutions is an ongoing trend because of the huge optimisation potentials it offers. On the other hand, however, the emergence of 6G as a multi-composite architecture building on different technologies unified together introduces new challenges in deploying effective and sustainable network automatisation mechanisms. This problem is even more important in the case of converged NTN-B5G networks, where the peculiarities of satellite systems make the overall network automation more challenging. This paper surveys the approach taken by the HE SNS-funded 5G-STARDUST project with respect to radio resource management, network slicing\/orchestration and NFV placement, as well as multi-connectivity support, by providing interesting insights on a data-driven approach distributed across space and ground segments.<\/p>\n

    16:35 – 16:55: Talk by Engin Zeydan,<\/strong> CTTC, Luis Blanco, <\/strong>CTTC, Cristian Jesus Vaca Rubio,<\/strong> CTTC, Jorge Baranda, <\/strong>CTTC, Albert Bel, <\/strong>CTTC, Farhana Javed, <\/strong>CTTC, Pol<\/strong> Henarejos, <\/strong>CTTC, Horacio Bleda, <\/strong>CTTC, Josep Mangues, <\/strong>CTTC, Selva Via, <\/strong>CTTC
    \n<\/strong><\/p>\n

    Title of the talk:
    \nNetwork Resource Management for Unified 6G Network: The UNITY-6G Approach
    \nThis paper presents the UNITY-6G architecture, a unified framework for end-to-end resource management across integrated terrestrial and non-terrestrial networks. UNITY-6G leverages a multi-layered design composed of physical infrastructure, network resource abstraction, service-based control, intelligent agentic AI, and blockchain-enabled security mechanisms. The proposed framework enables dynamic orchestration through distributed AI agents (local, regional, global) that adaptively coordinate resource allocation and optimization tasks. Service- Based Architecture (SBA) components provide modular and programmable control of core network functions, while blockchain technologies ensure trust, transparency, and secure auditing of operations. The architecture supports emerging use cases such as immersive Extended Reality (XR), energy management and industrial automation by aligning network intelligence with application requirements.<\/p>\n

    16:55 – 17:15: Talk by Milos Gravara<\/strong>, TU Wien, Andrija Stanisic, <\/strong>TU Wien, Stefan Nastic<\/strong>, TU Wien<\/p>\n

    Title of the talk:
    \nA Novel Compound AI Model for 6G Networks in 3D Continuum
    \nThe 3D continuum presents a complex environment that spans the terrestrial, aerial and space domains, with 6G networks serving as a key enabling technology. Current AI approaches for network management rely on monolithic models that fail to capture cross-domain interactions, lack adaptability, and demand prohibitive computational resources. This paper presents a formal model of Compound AI systems, introducing \u202fnovel tripartite framework that decomposes complex tasks into specialized, interoperable modules. The proposed modular architecture provides essential capabilities to address the unique challenges of 6G networks in the 3D continuum, where heterogeneous components require coordinated, yet distributed, intelligence. This approach introduces a fundamental trade-off between model and system performance, which must be carefully addressed. Furthermore, we identify key challenges faced by Compound AI systems within 6G networks operating in the 3D continuum, including cross-domain resource orchestration, adaptation to dynamic topologies, and the maintenance of consistent AI service quality across heterogeneous environments.<\/p>\n

    17:15 – 17:30: Talk by Elli Kartsakli<\/strong>, BSC, Nikolaos Bartzoudis<\/strong>, CTTC, Angelos Antonopoulos<\/strong>, Nearby Computing, Fred Buining<\/strong>, HIRO-MicroDataCenters BV, Thijs Metsch<\/strong>, Intel Deutschland GmbH, Joan Pujol Roig<\/strong>, Samsung UK, Semiha Kosu<\/strong>, Turkcell, Yansha Deng<\/strong>, KCL, Jordi P\u00e9rez-Romero<\/strong>, UPC, Oriol Sallent<\/strong>, UPC<\/p>\n

    Title of the talk:
    \nEdge4AI: Enabling Intelligent Edge Automation and AI Lifecycle Management for Beyond 5G Networks
    \nEdge computing is a key enabling technology expected to play a crucial role in beyond 5G (B5G) and 6G communication networks. The EU-funded VERGE contributes to the evolution of edge computing by promoting an open, modular and distributed edge architecture that enhances B5G capabilities and supports next generation services. This paper highlights the core features of VERGE\u2019s “Edge for AI” pillar, which enables closed-loop automation and life cycle management (LCM) of cloud-native applications and network services across a unified edge-to-cloud compute continuum.<\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":0,"parent":521,"menu_order":45,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-12058","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/pages\/12058","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/comments?post=12058"}],"version-history":[{"count":6,"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/pages\/12058\/revisions"}],"predecessor-version":[{"id":13276,"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/pages\/12058\/revisions\/13276"}],"up":[{"embeddable":true,"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/pages\/521"}],"wp:attachment":[{"href":"https:\/\/www.eucnc.eu\/wp-json\/wp\/v2\/media?parent=12058"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}