This chapter discusses the ways that Artificial Intelligence (AI) enhances sustainable wireless network management by enabling intelligent, automated, and adaptive control of resources. It addressed the application of AI, including techniques such as machine learning, deep learning, and reinforcement learning, to reduce energy consumption by parties utilizing dynamic resource allocation and infrastructure while maintaining service criteria. The use of AI with coordination pathways via software-defined networking (SDN) network function virtualization (NFV) would enable more real-time adaptations and energy savings. AI also creates potential for future applications of those or advanced concepts, such as federated learning and edge AI; the former provides user privacy and lessens energy use. We also elaborate on several challenges, such as data availability, model interpretability, and sustaining a delicate balance of sustainability and performance. In summary, we highlight the scope of AI advancements for promoting intelligent, sustainable wireless networks today, in 5G, 6G, or even more future paradigms.
Artificial intelligence for sustainable wireless network management: Models, strategies, and optimization
Randieri C.
2026-01-01
Abstract
This chapter discusses the ways that Artificial Intelligence (AI) enhances sustainable wireless network management by enabling intelligent, automated, and adaptive control of resources. It addressed the application of AI, including techniques such as machine learning, deep learning, and reinforcement learning, to reduce energy consumption by parties utilizing dynamic resource allocation and infrastructure while maintaining service criteria. The use of AI with coordination pathways via software-defined networking (SDN) network function virtualization (NFV) would enable more real-time adaptations and energy savings. AI also creates potential for future applications of those or advanced concepts, such as federated learning and edge AI; the former provides user privacy and lessens energy use. We also elaborate on several challenges, such as data availability, model interpretability, and sustaining a delicate balance of sustainability and performance. In summary, we highlight the scope of AI advancements for promoting intelligent, sustainable wireless networks today, in 5G, 6G, or even more future paradigms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


