TY - BOOK
T1 - Large Language Models in the 6G-Enabled Computing Continuum
T2 - a White Paper
AU - Abel, Markus
AU - Ahmad, Ijaz
AU - Casado, Constantino Alvarez
AU - Berner, Rico
AU - Bettinelli, Mickaël
AU - Björk, Kaj Mikael
AU - Capobianco, Michele
AU - Gross, James
AU - Nguyen, Tri Hong
AU - Hui, Pan
AU - Kostakos, Panos
AU - Kumar, Abhishek
AU - Laakkonen, Mika-Petri
AU - Liu, Xiaoli
AU - Liu, Zhi
AU - Nguyen,, Le
AU - Nguyen, Huong
AU - Ozparlak, Basak Ozan
AU - Pietiläinen, Ville
AU - Pirttikangas, Susanna
AU - Plassart, Stéphan
AU - Pyysalo, Sampo
AU - Ribouh, Soheyb
AU - Rinne, Jari
AU - Safanpour, Mehdi
AU - Saleh, Alaa
AU - Sheikhi, Saeid
AU - Silvén, Olli
AU - Souris, Harry
AU - Su, Xiang
AU - Suomalainen, Roope
AU - Vasilakos, Athanasios V.
AU - Zavodovski, Aleksandr
AU - Zhang, Qi
AU - Zhou, Peng Yuan
AU - Zourmand, Alireza
PY - 2025/1/24
Y1 - 2025/1/24
N2 - 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.
AB - 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.
KW - 6G
KW - Generative AI
KW - Large Language Model (LLM)
KW - Generative Pre-trained Transformers (GPT)
KW - Edge Intelligence
KW - Open RAN (O-RAN)
KW - AI RAN
KW - telecommunications technology
KW - generative artificial intelligence
KW - language models
KW - transformers
KW - artificial intelligence
KW - data communications networks
KW - machine learning
KW - mobile communication networks
KW - wireless data transmission
KW - information networks
M3 - Commissioned report
SN - 978-952-62-4375-7
T3 - 6G Research Visions
BT - Large Language Models in the 6G-Enabled Computing Continuum
PB - Oulun yliopisto
CY - Oulu
ER -