As the digital world moves towards more complex and powerful network infrastructures, AI and ML are increasingly seen as critical enablers for improving efficiency, scalability, and performance across all network layers. These technologies are instrumental in addressing the growing demands for ultra-low latency, high data rates, massive connectivity, and energy-efficient networks that 5G/6G and future networks promise.
Following the successful publication of five special issues on the theme of AI/ML in 5G and future networks, the ITU Journal on Future and Evolving Technologies (ITU J-FET) is launching this new call for papers.
In recent years, AI and ML are moving from enablers of single-use case solutions to ubiquitously deployed technologies for multiple use cases, such as singular and multi-agentic approaches. Other examples are part of network support and validation tools, such as digital twins. A shift is also being seen from the deployment of pre-trained models, to models which are being trained or updated within the network to responds to dynamic operational environments or differing hardware resources across the network. Together, this is supporting networks where AI is a first-class entity in its planning, management, and operation: AI-Native networks.
This special issue invites papers that offer novel insights and cutting-edge solutions for using AI and ML to revolutionize communication networks, accelerating innovation in 5G evolution, 6G vision, and future network systems. We welcome contributions that push the boundaries of current AI/ML applications in network design, optimization, and management.
6G, AI-native networks, generative AI (GenAI), digital twin, integrated sensing and communication (ISAC), machine learning (ML), beyond 5G
