6G Intelligence
Book chapter, 2026
This chapter provides an overview of the role of artificial intelligence (AI) and machine learning (ML) in advancing 6G networks, emphasizing their impact across multiple layers of the 6G system. It discusses the motivations for AI/ML adoption within 6G, including data-driven architecture, enhancements in physical layer performance, and AI-driven management and orchestration (M&O). The chapter also addresses trustworthiness, highlighting AI/ML’s role in security, privacy, and reliability. Additionally, it covers key enablers such as AI-driven radio air interface, network optimization strategies, and AI-driven intent-based service management, alongside relevant standardization efforts within 3rd Generation Partnership Project (3GPP) and O-RAN to ensure interoperability and scalability in future networks.
ML
artificial intelligence
MLOP
AI
6G
life cycle management
digital twin
reinforcement learning
AIaaS
ISAC
machine learning
AI-driven management and orchestration
LCM
AI-driven radio air interface
Author
Hamed Farhadi
Ericsson
Dani Korpi
Nokia
Nabeel Nisar Bhat
University of Antwerp
Pawani Porambage
Technical Research Centre of Finland (VTT)
Halina Tarasiuk
Warsaw University of Technology
Marcin Ziółkowski
Warsaw University of Technology
Karol Kuczyński
Warsaw University of Technology
José Miguel Mateos Ramos
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Christian Häger
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Henk Wymeersch
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Ricard Vilalta
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Merve Saimler
Ericsson
Leyli Karacay
Ericsson
Milan Zivkovic
Apple
6G to Build a Sustainable Futur
217-252
9781394363575 (ISBN)
Subject Categories (SSIF 2025)
Communication Systems
Computer Sciences
DOI
10.1002/9781394363605.ch6