Research & Development
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MACHINE LEARNING-BASED, NETWORKING AND COMPUTING INFRASTRUCTURE RESOURCE MANAGEMENT OF 5G AND BEYOND INTELLIGENT NETWORKS

Duration: 01/01/2021 - 31/12/2023

Total funding: EUR 6,126,684.00

Challenge & Objectives

MARSAL aims to provide an evolved architecture towards Beyond 5G (B5G), offering unprecedented degrees of flexibility and closed-loop autonomy at all tiers of the infrastructure, and significantly improved Spectral Efficiency via Cell-Free Networking. MARSAL project will generate the following outcomes:

  • Design and demonstrate scalable, distributed cell-free massive-MIMO networks supporting massive Access Points deployments.
  • Design and implement a cell-free virtual Radio Access Network for B5G, aligned with the O-RAN Alliance architecture.
  • Architect a disaggregated, Software-Defined-Networking control plane towards Fixed-Mobile Convergence.
  • Deployment of an Elastic Edge Computing paradigm with Cloud-Native technologies.
  • Policy-driven security, privacy and trust in multi-tenant infrastructures.
  • Deliver a Self-driven infrastructure with pervasive, Machine-Learning-driven control.
  • Implementation and proof-of-concept of the MARSAL solutions.
  • Dissemination, standardization and exploitation of MARSAL.

 

eBOS will work on AI-based solutions for malicious nodes detection. eBOS will lead the project dissemination following the strategy defined in Work Package 7. eBOS will set up the appropriate mechanisms and tools for maximum visibility and impact, ensuring that all partners contribute to dissemination activities, and assess the dissemination results.

 

Consortium

CENTRE TECNOLOGIC DE TELECOMUNICACIONS DE CATALUNYA

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IQUADRAT INFORMATICA SL

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KATHOLIEKE UNIVERSITEIT LEUVEN

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INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS

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NEC LABORATORIES EUROPE GMBH

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MELLANOX TECHNOLOGIES LTD - MLNX

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ORGANISMOS TILEPIKOINONION TIS ELLADOS OTE AE

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INTRACOM SA TELECOM SOLUTIONS

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EBOS TECHNOLOGIES LIMITED

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ORANGE SA

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UNIVERSITA DEGLI STUDI DI MILANO

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ACCELLERAN

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PIETRZYK SLAWOMIR

PHARROWTECH

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This project has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement No. 101017171.