Big AI Models in 5G Communication Technology, Cybersecurity, Metaverse, and Healthcare Services

Dear Colleagues,

This special issue mainly focuses on 5G technology it is already developed, it must be improved to meet the growing demands of modern society for applications like augmented and virtual reality and constant mobile communication. Over the previous few years, engineers have made considerable progress in inventing solutions that will push wireless networking and communication to new heights in the future. Green Internet of Things, digital twins, AI, semantic/goal-oriented communications, smart holographic/reflecting surfaces, and millimetre and terahertz spectrum are just a few examples. The advent of next-generation communication technology is expected to significantly boost the capacity and speed of our networks, allowing for more rapid and comprehensive data interchange and connectivity.

New methods for exploring these wireless data with specific forms of artificial intelligence (AI) are becoming available thanks to developments in machine learning and deep learning, paving the way for the successful completion of a wide range of Big, computation- or communication-oriented tasks, such as intelligent mobile edge computing, environment/object sensing, and intelligent wireless communication. Traditional techniques necessitate a unique AI model for each task because of the significant HW/SW overheads and the inability to delve deeply into the underlying correlation inside data and across jobs. Therefore, in light of the recent uptick in study in this area, the goal of this Special Issue (SI) is to bring together academic and industry experts to present cutting-edge developments in big AI models to the wireless communication community and to highlight numerous exciting prospects for future study across various disciplines especially biomedical and healthcare services. Here are some of the potential themes for this issue:

• Big AI model's effect on the cost of energy and networking.
• Big AI model architecture development for next-generation wireless systems.
• Developing wireless network protocols for Big AI adoption.
• Wireless networked distributed training of Big AI models that minimizes energy consumption.
• Big AI model's wireless network performance is thoroughly analyzed.
• Big data artificial intelligence model experiments, testbeds, and deployments over mobile networks.
• Concerns with massive AI models in wireless networks' privacy and security.
• Big artificial intelligence model for wireless semantic communications.
• Cooperative wireless sensing and communication using a Big AI model.
• Big AI model for intelligent mobile edge computing with several tasks.
• AI-based Zero Trust Models.
• Decentralized Zero Trust Models.
• Machine Learning and IOT in Wireless Networks.
• Cyberattacks and Risk Assessment, Standards in Wireless Networks
• Intelligent Mobile Edge Computing in Wireless Communications.
• AI/ML-based design and processing of intelligent/tensorial surfaces-aided communications.
• 5G and 6G Standardization.
• Blockchain and Cryptography.
• Security on Wireless and Mobile Networks.
• Threat and Vulnerability Analysis in Wireless Communication.
• Energy-Efficient Techniques for 5G Wireless Communication Technologies.
• Green Internet of Things Standards, Policy and Regulation.
• AI and optimization technologies in biomedical and healthcare services.
• 5G models and metaverse in remote healthcare services.

Dr. Saurav Mallik
Dr. Ruifeng Hu
Dr. Aimin Li
Guest Editors

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• machine learning
• wireless communication technology
• vulnerability
• mobile network
• artificial intelligence
• cyber attacks
• biomedical and health informatics