Machine Learning-Based, Networking and Computing Infrastructure Resource Management of 5G and Beyond Intelligent Networks

5G mobile networks will be soon available to handle all types of applications and to provide service to massive numbers of users. In this complex and dynamic network ecosystem, an end-to-end performance analysis and optimization will be the key features, in order to effectively manage the diverse requirements imposed by multiple vertical industries over the same shared infrastructure.

Objectives

1

Design and demonstrate scalable, distributed cell-free massive-MIMO networks supporting massive AP deployments.

2

Design and implement a cell-free vRAN for B5G, aligned with the O-RAN Alliance architecture.

3

Architect a disaggregated, SDN control plane towards Fixed-Mobile Convergence.

4

Deployment of an Elastic Edge Computing paradigm with Cloud-Native technologies.

5

Policy-driven security, privacy and trust in multi-tenant infrastructures.

6

Deliver a Self-driven infrastructure with pervasive, ML-driven control.

7

Implementation and proof-of-concept of the MARSAL solutions.

8

Dissemination, standardization and exploitation of MARSAL.

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Project Coordinated by:

Consortium

Project Coordinator

Dr. John Vardakas (IQU)

Project Co-Coordinator

Dr. Christos Verikoukis (IQU)

Project Manager

Melani Gurdiel (IQU)

Technical Manager

Dr. John Vardakas (IQU)

Innovation Manager

Dr. Ioannis Chochliouros (OTE)