Large Language Models in the 6G-Enabled Computing Continuum: a White Paper

Markus Abel, Ijaz Ahmad, Constantino Álvarez Casado, Rico Berner, Mickaël Bettinelli, Kaj-Mikael Björk, Michele Capobianco, James Gross, Hong-Tri Nguyen, Pan Hui, Panos Kostakos, Abhishek Kumar, Mika-Petri Laakkonen, Xiaoli Liu, Zhi Liu, Le Nguyen, Huong Nguyen, Basak Ozan Ozparlak, Ville Pietiläinen, Susanna PirttikangasStéphan Plassart, Sampo Pyysalo, Soheyb Ribouh, Jari Rinne, Mehdi Safanpour, Alaa Saleh, Saeid Sheikhi, Olli Silven, Harry Souris, Xiang Su, Roope Suomalainen, Athanasios V. Vasilakos, Aleksandr Zavodovski, Qi Zhang, Peng Yuan Zhou, Alireza Zourmand

Research output: Book/ReportCommissioned report

Abstract

The evolution towards 6G architecture will shift communication networks, with artificial intelligence (AI) playing a key role. This white paper examines the integration of Large Language Models (LLMs) within 6G systems. Their ability to grasp intent, reason, and plan, and execute commands will redefine network functionalities and interactions. An essential component is the AI Interconnect framework, designed to facilitate AI operations within the network. Building on the evolving state-of-the-art, we present a new architectural perspective for the next generation of mobile networks. Here, LLMs will work together with pre-generative AI and machine learning (ML) algorithms. This union combines old and new methods, merging established approaches with AI technologies. We provide an overview of this evolution and explore the applications arising from such an integration. We envisage an integration where AI becomes central to future communication networks, offering insight into the structure and function of a 6G network centered on AI.
Original languageEnglish
PublisherUniversity of Oulu
Number of pages74
ISBN (Electronic)978-952-62-4376-4
ISBN (Print)978-952-62-4375-7
Publication statusPublished - 2024
MoE publication typeD4 Published development or research report or study

Publication series

Name6G Research Visions
PublisherUniversity of Oulu
Volume14
ISSN (Print)2669-9621
ISSN (Electronic)2669-963X

Fingerprint

Dive into the research topics of 'Large Language Models in the 6G-Enabled Computing Continuum: a White Paper'. Together they form a unique fingerprint.

Cite this