Call for Papers

The fifth generation (5G) wireless communications are expected to satisfy the diverse service requirements in various aspects of our daily life, from residence, work, leisure, to transportation. Due to the extreme range of 5G requirements for user experience, efficiency, performance and complex network environments, the design and optimization of 5G networks becomes very challenging. The future 5G network will require robust intelligent algorithms to adapt network protocols and resource management for different services in different scenarios. Artificial intelligence (AI), which is defined as any process or device that perceives its environment and take actions that maximize the chances of success for some predefined goal, is a feasible solution for the emerging complex communication system design. The recent advances in deep learning, convolutional neural networks and reinforcement learning hold significant promise for solving very complex problems considered intractable until now. It is now appropriate to apply AI technology to 5G wireless communications to tackle optimized physical layer design, complicated decision making, network management and resource optimization tasks in such networks. Moreover, the emerging big data technology has brought us an excellent opportunity to study the essential characteristics of wireless networks, and to help us to obtain more clear and in-depth knowledge of the behavior of 5G wireless networks. In the study of 5G wireless technologies and communication systems, AI will be a powerful tool and hot research topic with many potential application areas, e.g., wireless signal processing, channel modeling, and resource management.

This IEEE Communications Magazine Feature Topic (FT) aims to provide a comprehensive overview of the state-of-the-art development in technology, regulation and theory for “applications of artificial intelligence in wireless communications," and to present a holistic view of research challenges and opportunities in the coming area of 5G wireless communications. Suggested topics include but are not limited to the following:

• Novel design of deep-learning and convolutional neural network approaches for wireless system applications and services.
• Novel design of machine-learning and pattern recognition algorithms for wireless communication technologies.
• Applications of AI for optimizing wireless communication systems, including channel models, channel state estimation, beamforming, code book design and signal processing.
• Applications of AI for 5G wireless transmission technologies, including coordinated multiple points transmission/reception, large scale antenna array, and multi-hop relay.
• Applications of AI for 5G mobile management, including user association, handoff strategy, and backhaul technology.
• Applications of AI for 5G resource management, including spectrum resources, energy sources, cloud resources, computing resources, and communication infrastructure.
• The analysis and prediction of 5G network behaviour via AI technologies, including the multi-media traffic load, network overhead, and network collision.
• Evaluating the scope for and potential limitations of AI solutions in wireless communications.

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Manuscript Submission Guidelines.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the "March 2019/Applications of Artificial Intelligence in Wireless Communications" topic from the drop-down menu of Topic/Series titles.

Important Dates

Manuscript Submission Deadline: August 1, 2018
Decision Notification: December 1, 2018
Final Manuscript Due: January 1, 2018
Publication Date: March 2019

Guest Editors

Xiaohu Ge
Huazhong University of Science and Technology, Wuhan, China

John Thompson
The University of Edinburgh, Scotland, UK

Yonghui Li
University of Sydney, Australia

Xue (Steve) Liu
McGill University, Montreal, Canada

Weiyi (Max) Zhang
AT&T Labs Research, Middletown, USA

Tao Chen
VTT Technical Research Centre of Finland Ltd., Oulu Finland