Artificial Intelligence-Enabled Intelligent 6G Networks
Helin Yang, Arokiaswami Alphones, Zehui Xiong, Dusit Niyato, Jun Zhao,, Kaishun Wu

TL;DR
This paper proposes an AI-enabled architecture for 6G networks that enhances performance through intelligent sensing, data analytics, control, and applications, addressing future demands with innovative AI techniques.
Contribution
It introduces a four-layer AI-enabled architecture for 6G networks and discusses how AI techniques can optimize network performance and guide future research directions.
Findings
AI-empowered mobile edge computing improves latency.
Intelligent mobility and handover management enhance user experience.
Smart spectrum management increases spectral efficiency.
Abstract
With the rapid development of smart terminals and infrastructures, as well as diversified applications (e.g., virtual and augmented reality, remote surgery and holographic projection) with colorful requirements, current networks (e.g., 4G and upcoming 5G networks) may not be able to completely meet quickly rising traffic demands. Accordingly, efforts from both industry and academia have already been put to the research on 6G networks. Recently, artificial intelligence (AI) has been utilized as a new paradigm for the design and optimization of 6G networks with a high level of intelligence. Therefore, this article proposes an AI-enabled intelligent architecture for 6G networks to realize knowledge discovery, smart resource management, automatic network adjustment and intelligent service provisioning, where the architecture is divided into four layers: intelligent sensing layer, data…
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