Call for Papers

6G networking research aims at addressing a large variety of requirements, and resulting in ubiquitous connectivity with the adequate, application-inferred, level of quality as well as AI-fueled 6G network automation. Built upon 6G mobile networks, many novel applications and services will emerge, ranging from extended reality (XR), immersive multimedia to industry 4.0 and beyond, autonomous driving, and Metaverses. Various state-of-the-art technologies should be employed to accommodate the requirements raised by such applications, e.g., multi-access edge computing (MEC) and AI techniques. In addition, 6G network design and operation are likely to take advantage of real-time interaction and synchronization between physical systems and their virtual image to assess the efficiency of the design and the operational procedures in a deterministic fashion, based upon Digital Twin techniques.

Digital Twin (DT) is a highly promising technology that can apply to elementary components as well as more complex systems. DT aims at providing a virtual image of a physical entity or system to model a design, validate a policy or assess the behavior of an entity or a system. A digital twin is the real-time digital replica of a real-world object, which connects physical systems and digital spaces. Digital twin can monitor, design, simulate, analyze, optimize and predict the behavior of physical systems. The use of digital twin for 6G is in particular motivated by the need to assess the adequacy and the efficiency of Quality-of-Service policies as well as the design and the operation of innovative services. Maintenance costs and security risks raised by physical systems can also be better mastered thanks to DT. DT applied to 6G networks has thus become part of the scope of 6G research, but is also the subject of standardization activities. The use of DT for 6G networks inevitably raises unprecedented challenges. For example, there are still many open research questions related to efficiency, accuracy, fault tolerance, and security. This Special Issue (SI) of the IEEE Network intends to attract contributions from both the academia and the industry and is meant to expose the most recent advances in integrated design, planning, and optimization of digital twin for 6G networks. Possible topics include, but are not limited to:

• Novel digital twin architecture and protocols for 6G
• Digital twin edge networks (DITEN) in 6G
• Digital twin networking for 6G
• Scalable, lightweight, and fault-tolerant digital twin for 6G
• Energy-efficient and low-latency digital twin in 6G
• AI/Machine learning for digital twin in 6G
• Edge association, adaptive edge association, digital twin transfer
• Digital twin for resource management and network optimization in 6G
• Security and privacy for digital twin empowered 6G
• Innovative digital twin applications and services for 6G
• DT usage for automated cross-domain 6G network and service production
• Digital twin for mobile vertical domain, e.g., digital twin for converged OT (operational technology) and ICT
• Hardware, software, platforms for digital twin systems in 6G
• Simulations, prototype, and testbeds for digital twin empowered 6G

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the "Information for Author" section of the Paper Submission Guidelines.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select “March 2023/Digital Twin for 6G Networks” from the drop-down menu of Topic titles.

Important Dates

Manuscript Submission Deadline: 15 October 2022
Initial Decision Notification: 30 November 2022
Revised Manuscript Due: 31 December 2022
Final Decision Notification: 20 January 2023
Final Manuscript Due: 31 January 2023
Publication Date: March/April 2023

Guest Editors

Yan Zhang
University of Oslo, Norway

Christian Jacquenet
Orange, France

Xueli An
Huawei Technologies, Germany

Nakjung Choi
Bell Labs, Nokia, USA

Yunlong Lu
Beijing Jiaotong University, China

Ramona Trestian
Middlesex University, UK

Sunghyun Choi
Samsung, Korea