Introduction

Evolving wireless networks and sensing technologies are integral components of modern communication and information systems. It has the potential to further transform industries, enhance our daily lives, and address critical global challenges. Since 6G communication represents the next generation of wireless technology and is expected to further revolutionize the digital ecosystem. 6G will likely harness the untapped potential of the terahertz (THZ) frequencies. These extremely high-frequency bands offer vast bandwidths and can support data rates in the terabits per second. THz communication will enable new applications (like healthcare, agriculture, and environmental monitoring) in immersive extended reality (XR), high-resolution imaging, and precise sensing. In addition, 6G communication is still in the early stages of research and development, and it is expected to become commercially available in the 2030s. As it evolves, it will empower a new wave of innovations, enhance the digital ecosystem, and impact various aspects of our lives and industries. Artificial intelligence (AI) will play a central role in 6G networks. AI will be used for network optimization, security, enhancing user experiences, etc. Additionally, AI will be integrated into edge devices, making them smarter and more efficient.

Developing technology for 6G, which is expected to be significantly more advanced than 5G, is a major challenge that includes signal propagation, increased energy consumption, security and privacy, regulatory and spectrum allocation, and many more. Integrating 6G with emerging technologies like AI, IoT, and quantum computing presents challenges in terms of compatibility, performance, and synergy. Future trends in AI-powered wireless networks and sensing technologies are poised to bring about significant advancements in connectivity, automation, and data processing and are anticipated as key factors in shaping the digital ecosystem. AI-driven 6G networks will provide real-time, ultra-reliable connectivity to ensure safe and efficient autonomous systems. AI will help in the design of an environmentally friendly network infrastructure that will align with the broader trend toward sustainability in technology and facilitate seamless 6G communication. In essence, AI is not just evolving within the digital ecosystem; it's reshaping the landscape, offering new possibilities and improving efficiency in countless domains. As this technology continues to evolve, it will undoubtedly play a pivotal role in shaping our digital future.

The special issue on "Future Trends of AI Empowered Wireless Networks and Sensing Technologies in 6G Communication for Digital Ecosystem" serves as a platform to explore the forefront of technological innovation, as 6G communication is expected to be the next major leap in wireless connectivity. We welcome researchers, experts, and industry leaders to share their insights and findings, ultimately contributing to the development of cutting-edge solutions for a more connected, efficient, and sustainable digital future.

Recommended topics (but not limited to)

• AI algorithms-based 6G-powered wireless sensor networks for smart city digital ecosystems
• AI-based next-gen wireless sensor networks (WSN) in the 6G digital ecosystem: recent advancements, applications, challenges, and future trends
• AI-enabled efficient interference management of 6G and beyond networks for digital ecosystem applications
• AI-powered service-oriented architecture (SOA) in 6G WSNs for digital health ecosystems
• Future trends of AI in hyperconnected ecosystems for secure digital business and applications
• Evolving AI-assisted reconfigurable intelligent surfaces with 6G and beyond for multi-functional digital manufacturing
• AI-enabled seamless integration of 6G THz wireless communication technology for a resilient digital infrastructure
• AI-based scheme in physical layer security of 6G wireless communication and sensing networks for the future of risk management
• Future developments of AI-based 6G cognitive wireless networks and sensing systems for smart energy system
• Testbeds and future trends in AI-empowered 6G and B6G networks for digital transformation and applications
• AI advances in antenna technology for reliable 6G and B6G networks: novel results, use cases, control and power efficiency

Important dates

Submission deadline: 31 August, 2024

Authors notification:  30 November, 2024

Revision submission: 31 January, 2025

Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.

During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

Guest Editors

Lead: Prof. Sotirios K. Goudos, Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece, email: skgoudo@ieee.org

Sotirios K. Goudos received the B.Sc. degree in physics, the M.Sc. degree in electronics, and the Ph.D. degree in physics from the Aristotle University of Thessaloniki, in 1991, 1994, and 2001, respectively, the master’s degree in information systems from the University of Macedonia, Greece, in 2005, and the Diploma degree in electrical and computer engineering from the Aristotle University of Thessaloniki, in 2011. He joined the Department of Physics, Aristotle University of Thessaloniki, in 2013, where he is currently an Associate Professor. He is the Director of the ELEDIA@AUTH Laboratory Member of the ELEDIA Research Center Network. He is the author of the book Emerging Evolutionary Algorithms for Antennas and Wireless Communications (Institution of Engineering & Technology, 2021). His research interests include antenna and microwave structures design, evolutionary algorithms, wireless communications, and semantic web technologies. He is a member of the IEICE, the Greek Physics Society, the Technical Chamber of Greece, and the Greek Computer Society. He is the Founding Editor-in-Chief of the Telecom open access journal (MDPI publishing). He is also serving as an Associate Editor for the IEEE Transactions on Antennas and Propagation, IEEE Access, and the IEEE Open Journal of the Communication Society. He is also member of the Editorial Board of the International Journal of Antennas and Propagation (IJAP), the Electronics open access journal (Microwave and Wireless Communications Section), and the International Journal on Advances on Intelligent Systems. He was honored as an IEEE Access Outstanding Associate Editor for 2019, 2020, and 2021. He is also serving as the IEEE Greece Section Secretary.

Prof. Shaohua Wan, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China, email: shwanhust@gmail.com

Prof. Shaohua Wan, Shaohua Wan received the Ph.D. degree from the School of Computer, Wuhan University, in 2010. He is currently a Professor with the Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China. From 2016 to 2017, he was a Visiting Professor with the Department of Electrical and Computer Engineering, Technical University of Munich, Germany. He is the author of over 150 peer-reviewed research articles and books, including over 40 IEEE/ACM Transactions articles such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Intelligent Transportation Systems, ACM TOIT, IEEE Transactions on Network Science and Engineering, IEEE Transactions on Multimedia, IEEE Transactions on Computational Social Systems, ACM TOMM, IEEE Transactions on Emerging Topics in Computational Intelligence, and PR, and many top conference papers in the fields of edge intelligence. His main research interest includes deep learning for the Internet of Things.

Prof. Mohammad A. Matin, Department of Electrical and Computer Engineering at North South University, Bangladesh, email: matin.mnt@gmail.com

Prof. Mohammad Abdul Matin, Mohammad Abdul Matin received the B.Sc. degree in electrical and electronic engineering from BUET, Bangladesh, the M.Sc. degree in digital communication from Loughborough University, U.K., and the Ph.D. degree in wireless communication from Newcastle University, U.K. He has been a Professor with the Department of Electrical and Computer Engineering, North South University (NSU), since 2008. He has published over 120 peer-reviewed journals and conference papers. He is the author/editor of 17 academic books and 21 book chapters. He serves as a member for the Editorial Board for several international journals, including IEEE Communications Magazine and IET Wireless Sensor Systems. He has received a number of prizes and scholarships, including the Best Student Prize (Loughborough University), Commonwealth Scholarship, and Overseas Research Scholarship (ORS) conferred by the Committee of Vice Chancellors and Principals (CVCP) in the U.K.

Dr. Seyyedali Hosseinalipour, Department of Electrical Engineering, University at Buffalo, USA, email: s.ali.alipour@gmail.com

I am an assistant professsor in the Department of Electrical Engineering at the University at Buffalo, SUNY. I was a postdoctoral associate at the School of Electrical and Computer Engineering of Purdue University, working under supervision of Prof. Mung Chiang and Prof. Christopher Brinton from 2020 to 2022. I received my M.Sc. and Ph. D. degree from North Carolina State University, Raleigh, NC, USA, in 2017 and 2020, respectively, both in electrical engineering, under the supervision of Prof. Huaiyu Dai. Prior to that I recived my B.Sc. degree from Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran, in 2015 in electrical engineering with minor in applied mathematics. My research interest includes, Machine learning for wireless networks, Machine learning by wireless networks, Unmanned aerial vehicle (UAV)-assisted wireless networks, Distributed and cloud computing, and Emerging technologies such as intelligent reflecting surface and mobile edge computing.