6G Technology
A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 1280
Special Issue Editors
Interests: antenna design; microwave component design; wireless communications; evolutionary algorithms; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: telecommunication networks; internet of things; network security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The sixth generation (6G) of cellular communications will serve as a pivotal enabling technology for both the contemporary and future information society. Sixth-generation network systems will provide customers with data rates exceeding several Gbps, and will facilitate the operation of new apps on mobile devices. In fact, 6G is expected to extend 5G capabilities even further. Higher bitrates (up to Tbps) and lower latency (less than 1 ms) will allow for the introduction of new services. There exists an industry-wide consensus that 6G is expected to launch around 2030 with a new spectrum in frequency range 3 (FR3), which spans 7.125–24.25 GHz. At the same time, new antenna systems, such as pinching and fluid antennas, are emerging for 6G networks.
Artificial intelligence (AI), terahertz (THz) communication, optical wireless communication, intelligent reflective surfaces, integration with nonterrestrial networks (NTN), blockchain, dynamic network slicing, cell-free communication, virtual/augmented reality (VR/AR), edge computing, and big data analytics are just some of the emerging technologies that are expected to drive 6G technology forward. Sixth-generation communication technology is projected to power novel applications such as holographic communications, tactile Internet, connected autonomous vehicles, unmanned aerial vehicles, autonomous healthcare and manufacturing systems, virtual/augmented/extended reality, etc.
Moreover, AI methodologies and techniques, including machine learning (ML), deep learning, and reinforcement learning, serve as essential facilitators for optimizing wireless network operations, improving the overall user experience, and delivering innovative service applications. Machine learning (ML) will be fundamental to ensuring the efficiency of future wireless communication networks, simultaneously acting as the enabling technology for various value-added applications and services. The application of machine learning in wireless communication nodes can facilitate various advanced services and enhance Quality of Service features for the proposed applications.
However, the investigation of 6G wireless technologies presents significant challenges. We invite original contributions describing the applications and experiences related to the emerging trends of 6G communication technologies. Potential topics include, but are not limited to, the following:
- Antenna systems for 6G systems.
- Non-terrestrial networks for 6G systems.
- Reconfigurable intelligent surfaces (RIS) for 6G networks.
- Integrated sensing and communications (ISAC) for 6G networks.
- Machine learning applications for 6G networks.
- Network design and optimization for 6G networks.
- THz communications as a 6G enabler.
- FR3 band communication.
- NOMA techniques for 6G networks.
- IoT for 6G networks.
- Vision, key drivers, new services, and requirements for 6G networks.
- System and network architectures for 6G technologies.
- Wireless backhaul and fronthaul solutions for 6G networks.
- Slicing for 6G networks.
- Intent-based systems and digital twinning applied in 6G networks.
- Network softwarization for 6G networks.
- Blockchain technology for 6G networks.
- Security for 6G networks.
- Vehicular networks for 6G technologies.
- Cell-free communication.
Prof. Dr. Sotirios K. Goudos
Dr. Panagiotis Sarigiannidis
Guest Editors
Manuscript Submission Information
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Keywords
- 6G technologies
- 6G applications
- terahertz
- edge computing
- artificial intelligence
- machine learning
- RIS
- antenna design
- NOMA
- FR3 band
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