Next-generation wireless networks are longed for an extreme support of high data rates and new innovative applications, and would be extremely dynamic and complex due to the ultra-dense deployment of heterogeneous networks and increasingly distributed data. This entails many critical challenges for network planning, operation, radio management, generation and consumption of wireless data, making the application and operation of future wireless networks even more complex. To satisfy the diverse requirements of next-generation wireless networks and mitigating the complexity of future network operation, it’s necessitating a new wireless technology paradigm, assisting the radio in intelligent adaptive learning and decision making and incorporating new approaches of intelligently utilizing distributed computational resources. Such communication requirements and the emerging fog computing and core intelligence can only be realized by integrating fundamental notions of artificial intelligence (AI) and machine learning across wireless infrastructure and end-user devices. In this context, this Special Track will discuss the concepts of machine learning, artificial intelligence (AI) and the promising artificial intelligence tools and their potential applications in next generation of wireless communication. Also it will provide a deep and comprehensive analysis on the utilization of these techniques and tools for efficient data acquisition, knowledge discovery, network planning, operation and management of the next generation wireless networks. In this Special Track, we are seeking submissions that focus on artificial Intelligence and machine learning applications for next generation wireless networks. This Track invites academic researchers in computer science, communication engineering, as well as information technology industry consultants and practitioners, to contribute original contributions in all aspects of learning, reasoning and decision-making mechanisms for designing a tightly integrated network and enhancing the efficiency of wireless network operation. The goal of this Special Track is to disseminate the latest research and innovations on machine learning algorithms and artificial intelligence applications in future wireless communication systems and networks.

This special Track solicits original work presented as research contribution, tutorial, or technical paper. Manuscripts should describe completed and unpublished work not currently under review elsewhere. Review papers on this topic are also welcome. Potential topics include, but are not limited to:

• AI and Machine Learning applications in future wireless communication
• Challenges of AI for wireless communications
• Learning schemes for resource management
• Machine learning for resource allocation in wireless networks
• Technologies for next-generation wireless communications
• Intelligent Spectrum management and Users Mobility Handling
• Channel estimation and Modeling
• Prediction methods on PHY applications for future wireless communications
• Optimization approaches and policies for wireless network control
• Applications on mobile edge computing and fog computing
• Model and knowledge driven deep learning technologies
• Neural networks for wireless communication links
• Data-driven optimization of wireless networks
• Distributed machine learning for wireless communications
• Deep reinforcement learning for wireless communications
• Machine learning based testbeds and experimental evaluations
• Machine learning for video caching and streaming over wireless networks

Important Dates:

Paper submission deadline: March 15, 2020

Notification of acceptance: April 19, 2020

Camera-ready due: May 3, 2020

Program Committee:

– Kuei-Ping Shih, Tamkang University, Taiwan

- Pascal Lorenz, University of Haute Alsace, France

– Pardeep Kumar, University of EST, Pakistan

- Parisa GHODOUS, Liris - Lyon, France – Mohammad Hammoudeh, Manchester University, UK

- Pardeep Kumar, University of Engineering, Science and Technology, Pakistan

– Antoine Bagula, University of the Western Cape, South Africa

- Mehmet Aydin, University of the West of England, UK

– Yahia SLIMANI, University of Manouba, Tunisia

– Paolo Bellavista, University of Bologna, Italy

– Janet Light Thompson, University of New Brunswick, Canada

– Doreen Böhnstedt, Technical University of Darmstadt, Germany

– Sohail Jabbar, Kyungpook National University, South Korea

– Vincenzo Gulisano, Chalmers University of Technology, Sweden

– Ignacio Bosch Roig, Polytechnic University of Valencia, Spain

– Angel Molina-Garcia, Universidad Politecnica de Cartagena, Spain

Track Chairs:

Dr. Mounir ARIOUA, National School of Applied Sciences, Abdelmalek Essaadi University, Morocco

E-Mail: m.arioua@uae.ac.ma

Dr. Mohamed LAZAAR, National School of Computer Science & Systems Analysis (ENSIAS), Mohammed V University, Morocco

E-Mail: lazaarmd@gmail.com