NEWTON aims at becoming one of the first MSCA-DN project that adopts novel techniques for scalable cell-free communications for 6G networks and advanced AI approaches for improved network performance, while being in-line with the ORAN approach.

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Test Post 3
The groundbreaking Horizon Europe project 6G-TERRAIN is now offering an extraordinary opportunity for aspiring researchers. Funded under the prestigious Horizon Europe – MSCA (Marie Skłodowska-Curie Actions) with Grant Agreement No. 101169346, the project is set to shape the future of telecommunications by developing an AI-native 6G system that seamlessly integrates terrestrial and non-terrestrial nodes. PhD OpportunitiesThe project is currently recruiting 10 PhD students with the unique opportunity to work at the forefront of 6G research and development. These doctoral positions will provide candidates with hands-on training and research opportunities in designing and implementing cutting-edge AI-driven systems. Application DetailsInterested candidates should submit their applications by March 31, 2025 via the official application portal: https://oaf.6g-terrain.eu/. Successful applicants will begin their doctoral positions starting from April 2025. Why Join 6G-TERRAIN? Be part of a Horizon Europe-funded project with global implications for telecommunications and AI. Contribute to the development of a pioneering AI-native automation architecture for 6G systems. Collaborate with leading researchers and institutions across Europe. This initiative represents an exceptional opportunity to contribute to cutting-edge innovation in telecommunications and AI, with the potential to shape the future of global connectivity. For more information, visit the project portal and take your first step towards being a part of this transformative journey. [...] Read more...

ABOUT

NEWTON proposes a revolutionary approach of a converged wireless-optical network architecture that makes reality an efficient 6G Cell-Free (CF)-based access network for high-density and high-coverage deployments. The proposed architecture takes also full advantage of novel solutions for both the radio-edge and regional-edge domains, as well as for efficient network-management approaches, targeting to achieve sub-second latency, more than 108 devices/Km2 connection density and user-experienced data-rate up to 10Gbps.
 
The proposed network architecture utilizes the advantages of the CF technology and the distributed neuromorphic paradigm at the edge, as well as novel MIMO schemes, optical X-haul design, and advanced AI-based methods for network management. Specifically, NEWTON aims at addressing a set of innovative challenges at the radio-edge, the regional-edge, and the network-management domains, targeting to propose a new approach on 6G networking, thus being perfectly matched with the technology roadmap of every major 5G/6G-related organization in the world.

CONSORTIUM

The Project consists of 9 partners from 7 European countries. It is well balanced in terms of research-industry collaboration as the consortium comprises 4 Universities/Research Institutes and 5 Industrial partners.
IQUADRAT Informática S.L.
ISI/ATHENA
University of Leuven
ISRD Sp. z o.o.
EURECOM
University of Western Attica
NVIDIA
Open University of Catalonia
RANPLAN Wireless

Funding
This project has received funding from the European Union’s Horizon Europe Research and Innovation Programme under Grant Agreement No 101169346. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

NEWS

  • Test Post 3
    The groundbreaking Horizon Europe project 6G-TERRAIN is now offering an extraordinary opportunity for aspiring researchers. Funded under the … Test Post 3Read more
  • Test Post 2!
    The groundbreaking Horizon Europe project 6G-TERRAIN is now offering an extraordinary opportunity for aspiring researchers. Funded under the … Test Post 2!Read more
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