Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective

Miltiadis C. Filippou Vasiliki Lamprousi Jafar Mohammadi Mattia Merluzzi Elif Ustundag Soykan Tamas Borsos Nandana Rajatheva Nuwanthika Rajapaksha Luc Le Magoarou Pietro Piscione Andras Benczur Quentin Lampin Guillaume Larue Dani Korpi Pietro Ducange Alessandro Renda Hamed Farhadi Johan Haraldson Leonardo Gomes Baltar Emilio Calvanese Strinati Panagiotis Demestichas Emrah Tomur

Intel Next Generation & Standards, Germany WINGS ICT Solutions, Greece Nokia Bell Labs, Germany CEA-Leti, UGA, France Ericsson Research, Turkey Ericsson Research, Hungary University of Oulu, Finland B<>COM, France Nextworks, Italy SZTAKI, Hungary Orange Research, France Nokia Bell Labs, Finland University of Pisa, Italy Ericsson Research,Sweden

July 21, 2022

AI6G’22: First International Workshop on Artificial Intelligence in beyond 5G and 6G Wireless Networks

Copyright Notice: 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

This work has been partly funded by the European Commission through the H2020 project Hexa-X (Grant Agreement no. 101015956).

Abstract

The European 6G flagship project Hexa-X has the objective to conduct exploratory research on the next generation of mobile networks with the intention to connect human, physical and digital worlds with a fabric of technology enablers. Within this scope, one of the main research challenges is the ambition for beyond 5G (B5G)/6G systems to support, enhance and enable real-time trustworthy control by transforming Artificial Intelligence (AI) / Machine Learning (ML) technologies into a vital and trusted tool for large-scale deployment of interconnected intelligence available to the wider society. Hence, the study and development of concepts and solutions enabling AI-driven communication and computation co-design for a B5G /6G communication system is required. This paper focuses on describing the possibilities that emerge with the application of AI & ML mechanisms (with emphasis on ML) to 6G networks, identifying the resulting challenges and proposing some potential solution approaches.

PDF viewer not supported. Download the PDF to view.