Committed to connecting the world

WTISD

Special issue on AI/ML solutions in 5G and future networks

​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

The​​​me 

The 2023 ITU AI/ML in 5G Challenge (Fourth edition) provides a collaborative platform for addressing challenges in the application of Artificial Intelligence (AI)/Machine Learning (ML) in emerging communication networks, including 5G and the forthcoming 6G. Participants, including students and professionals from over 100 countries, engage with industry and academia to tackle real-world problems using AI/ML in communication networks.

Since 2020, the ITU AI/ML in 5G Challenge offers carefully curated problem statements, a mix of real-world and simulated data, and mentoring including technical webinars and hands-on sessions. Teams participating in the Challenge enable, create, train, validate, and apply ML models for communication networks. This enables participants to not only showcase their talent, test their concepts on real data and real-world problems, and compete for global recognition including prize money and certificates, but also enter the world of ITU standards by mapping their solutions to ITU specifications.

Following the successful publication of three special issues on theme​ of AI and ML in 5G and future networks, the ITU Journal on Future and Evolving Technologies (ITU J-FET) is launching a new call for papers focused on research related to problem statements of the fourth edition of the Challenge. Therefore, we invite researchers to submit their works for consideration in a special issue of the ITU Journal. The invitation targets hosts and participants of the Challenge, and contributions based on novel research with clearly explained and strongly aligned topics in the challenge are also welcome. This dedicated edition aims to explore the impact of AI and ML in 5G/6G and future networks, along with the enabling technologies and tools within network infrastructures.

Keyw​​​ords

5G, beyond 5G, 6G, artificial intelligence, energy consumption, wireless communication systems, machine learning, deep learning

​Suggest topics (but not limited to)

​Download the FULL call for papers here.

Leading Guest Editor

​​​ Paul Harvey, University of Glasgow, UK  

​Guest Editors

Ilan Correa​, Federal University of Pará, Brazil
​​​ Antonio De Domenico, Huawei, France 
​​​ Steve Blandino, National Institute of Standards and Technology, USA 
​​​ Paola Soto-Arenas, Universiteit Antwerpen, Belgium  
​​​ Xiaojia Song, China Mobile, China  
​​​ Xi  Zheng, Huawei, China  
​​​ Bo Wei​, The University of Tokyo, Japan​