6G Intelligence
Kapitel i bok, 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
Författare
Hamed Farhadi
Ericsson AB
Dani Korpi
Nokia
Nabeel Nisar Bhat
Universiteit Antwerpen
Pawani Porambage
Teknologian Tutkimuskeskus (VTT)
Halina Tarasiuk
Politechnika Warszawska
Marcin Ziółkowski
Politechnika Warszawska
Karol Kuczyński
Politechnika Warszawska
José Miguel Mateos Ramos
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Christian Häger
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Henk Wymeersch
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Ricard Vilalta
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Merve Saimler
Ericsson AB
Leyli Karacay
Ericsson AB
Milan Zivkovic
Apple
6G to Build a Sustainable Futur
217-252
9781394363575 (ISBN)
Ämneskategorier (SSIF 2025)
Kommunikationssystem
Datavetenskap (datalogi)
DOI
10.1002/9781394363605.ch6