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Generative AI, an emerging paradigm for building a unified machine learning system based on a generic class of AI models, has received a lot of attention. It empowers users to rapidly produce diverse contents by leveraging a range of inputs. These inputs and outputs can encompass text, images, sounds, animation, 3D models, and various other types of data. For instance, generative pre-trained transformers (GPTs) have been successfully applied to natural language processing. On the one hand, it is interesting to study the use of generative AI in solving communication and networking problems in 5G-Advanced toward 6G. On the other hand, deploying generative AI models over wireless networks faces several key challenges, including the large-scale model parameter computation and transmission and the large amount of training data collection. Furthermore, due to the distributive nature of data and computing resources, deploying generative AI models over wireless networks may require collaboration of a large number of wireless devices and edge servers for training, inference, and tasks accomplishment purposes. Therefore, it is necessary to investigate novel network designs to support the deployment of generative AI models. How to make the training and deployment of generative AI models in a network robust, efficient, and sustainable is an urgent question that needs to be addressed in the foreseeable future.

This Special Issue (SI) aims to contribute to the development of a comprehensive understanding of the potentials and challenges of generative AI within the context of 5G-Advanced toward 6G communication networks, and to provide guidance for future research and development in this field. This SI is intended to be interdisciplinary, and contributions from a variety of fields, including computer science, electrical engineering, and communications engineering, are welcomed.

This SI on the interplay between generative AI and 5G-Advanced toward 6G aims to bring together a diverse range of contributions, covering both the theoretical and practical aspects of this field. Its scope includes, but is not limited to, the following topics:

• Generative AI for semantic communication over wireless networks.
• Generative AI for mobile edge computing.
• Generative AI for users’ behavior analysis and inference.
• Generative AI for wireless signal processing.
• Channel rendering, 3D mapping, and material learning.
• Integrated sensing, communications, and generative AI.
• Architecture design of generative AI in wireless networks.
• Energy-efficient training and inference of generative AI in wireless networks.
• Performance evaluation of generative AI in wireless networks.
• Vehicular, IoT, and other applications of generative AI in wireless networks. 
• Network protocol design, physical layer design, and resource allocation.
• Privacy and security issues.
• Standardization, interoperability, and testing.
• Testbeds, proof of concepts, field trials, and commercial deployments.

Submission Guidelines

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

All manuscripts to be considered for publication must be submitted by the deadline through the magazine’s Manuscript Central submission site. Select “July2024/GenerativeAIand5G6G” from the drop-down menu of Topic titles.

Important Dates

Manuscript Submission Deadline: 15 January 2024
Initial Decision Notification: 20 April 2024
Revised Manuscript Due: 20 May 2024
Final Decision Notification: 20 June 2024
Final Manuscript Due: 10 July 2024
Publication Date: September/October 2024

Guest Editors

Xingqin Lin
NVIDIA, USA

Mingzhe Chen
University of Miami, USA

Taesang Yoo
Qualcomm, USA

Yue Wang
Samsung, UK

Lina Bariah
Technology Innovation Institute, UAE

Nguyen H. Tran
The University of Sydney, Australia

Kaibin Huang
University of Hong Kong, China