A Survey on AI for 6G: Challenges and Opportunities
Constantina Chatzieleftheriou, Eirini Liotou

TL;DR
This survey reviews how AI technologies like deep learning and reinforcement learning support 6G networks, addressing challenges and exploring future research directions for high-performance wireless communication.
Contribution
It provides a comprehensive overview of AI's role in 6G, highlighting key technologies, integration with network functions, and future challenges and opportunities.
Findings
AI enables high data rates and low latency in 6G.
Challenges include scalability, security, and energy efficiency.
Future directions involve standardization and ethical considerations.
Abstract
As wireless communication evolves, each generation of networks brings new technologies that change how we connect and interact. Artificial Intelligence (AI) is becoming crucial in shaping the future of sixth-generation (6G) networks. By combining AI and Machine Learning (ML), 6G aims to offer high data rates, low latency, and extensive connectivity for applications including smart cities, autonomous systems, holographic telepresence, and the tactile internet. This paper provides a detailed overview of the role of AI in supporting 6G networks. It focuses on key technologies like deep learning, reinforcement learning, federated learning, and explainable AI. It also looks at how AI integrates with essential network functions and discusses challenges related to scalability, security, and energy efficiency, along with new solutions. Additionally, this work highlights perspectives that…
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