Call for Papers

Submit a Paper

Background and Motivation

Over the last couple of decades, the paradigm of virtualization has been evolving from a virtualized local area network (LAN) and private networks to the solidification of network function virtualization (NFV) and network slicing principles. This advancement is driven by the edge computing and cloudification capabilities of current wireless network generations. With the growing demands of wireless networks, in terms of latency, reliability, and energy and spectral efficiency, and the emergence of sophisticated services with heavy distributed computing requirements, it is envisaged that the concept of network virtualization will be scaling up from the node and link levels to the network-wide level, setting the scene for a holistic network virtualization, from the core to the edge. Coupled with the pervasive utilization of artificial intelligence (AI) at all network levels, the Digital Twin (DT) paradigm has been recently deemed as a promising tool for network design, optimization, management, and recovery, in which the DT can be leveraged to realize the vision of sustainable, zero-touch 6G networks. The key principle of the DT paradigm is to create a virtual representation, not only for the physical elements, but also for the dynamics and functions of the network. According to its definition, the DT is envisioned to enable end-to-end digitization of wireless networks, with the aim to perform cost- effective, adaptive, efficient, and fast network-wide optimization of the available resources and infrastructure design. Furthermore, the DT allows the utilization of the digital realm with the aim to develop and test novel schemes and AI algorithms, that are capable of handling previously experienced critical situations or predicted scenarios based on the collected data at the cyber twin, and then to implement them at the physical twin once fully mature.

Despite its promising advantages, to reap the full potential of the DT technology in 6G networks, the cyber twin is envisaged to leverage AI algorithms, with novel data-driven paradigms, high performance computing, optimization theory, matching theory, as well as efficient cyber-physical interaction schemes, among others, to realize the necessary adaptation/reconfiguration at the physical twin with an imperceptible time-lag. In order to achieve the needed quality-of-service (QoS) for the successful implementation of a high-fidelity DT paradigm in 6G, a new level of stringent requirements pertaining to connectivity, reliability, latency, and data rate are imposed on future wireless generations. It is worth highlighting that the research on the interplay of the DT and 6G networks is still in its early stages, and the reported contributions in this field are very limited. While the field of DT-enabled wireless communication is relatively new, it has attracted the attention from the research community in a short span of time. Inspired by this, the aim of this Feature Topic is to attract novel research contributions on DT-empowered wireless networks, and to be a stepping-stone on advancing the research on DT for 6G. Such an attractive and new topic is expected to attract a large number of researchers, who are interested in exploring the advancements in DT-enabled 6G and its technical limitations and challenges.

Topics and Scope

The objective of this Feature Topic (FT) is to solicit research papers with original contributions that address the latest advances and challenges in DT-empowered wireless networks, paving the way for the efficient realization of pervasive intelligent and holistic network virtualization in future 6G networks. More specifically, this FT will bring together leading researchers from both industry and academia to present their views on this emerging research with respect to the fundamentals, core design aspects, applications, use-cases, and challenges of DT-empowered wireless networks.

Topics of interest include, but are not limited to:

• The interplay of machine learning and DT in 6G networks.
• Security and Privacy in DT-enabled 6G.
• The interplay of DT and the Metaverse.
• DT-based resource allocation in 6G networks.
• Latency minimization in DT-enabled wireless networks.
• DT for intelligent surface-assisted wireless networks.
• DT-assisted task offloading.
• DT for high-frequency wireless networks.
• Wireless edge-empowered DT.
• DT for industrial IoT.
• Novel AI Algorithms and Architectures for efficient DT.
• DT-enabled vehicular networks.
• DT for zero-touch networks.
• The interplay of DT and network slicing.
• DT for optical wireless communication.
• DT for satellite-enabled wireless communication.
• Sustainable wireless networks through DT.
• URLLC in DT-enabled wireless networks.
• Testbed designs and implementation of DT in wireless networks.
• Network simulations of DT-enabled 6G.

Significance & Timeliness

While the research continues to argue what future wireless generations will be, it has become apparent that 6G wireless networks will be shaped towards provisioning network virtualization and softwarization, with the aim to support ubiquitous deployment of latency-sensitive applications. While ultra-high reliability and data rates are essential for the successful implementation of these applications, they require the development of online proactive mechanisms, in order to realize self-adaptive, self-optimizing, and self-sustaining networks, with intelligent inference and decision-making capabilities. In this regard, future wireless networks are envisioned to be DT-native. It is worthy to note that the research on the interplay of DT and wireless networks is relatively new and has not been well investigated in the recent literature, and therefore, there is a need to advance the research on the practical implementation, analysis, design and modeling, and applications, and to identify technical challenges of DT in 6G networks. Hence, the aim of this FT is to open the floor for exploring the potential advantages realized when integrating the DT paradigm in the design and optimization of future wireless networks. We strongly believe that such an attractive topic will be of a great interest for the research community, particularly, the communications society, and hence, it fits well within the IEEE Communications Magazine’s objectives.

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Manuscript Submission Guidelines. Please, check these guidelines carefully before submitting since submissions not complying with them will be administratively rejected without review.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the “FT-2222 / The Interplay of Digital Twin and 6G Wireless Networks” topic from the drop-down menu of Topic/Series titles. Please observe the dates specified here below noting that there will be no extension of submission deadline.

Important Dates

Manuscript Submission: 15 December 2022
First Round of Review Results Notification: 15 January 2023
Revised Papers Due: 15 February 2023
Final Acceptance Notification: 15 March 2023
Final Manuscript Due: 31 March 2023
Publication: June 2023

Guest Editors

Lina Bariah (Lead Guest Editor)
Technology Innovation Institute, UAE 

Mérouane Debbah
Technology Innovation Institute, UAE
CentraleSupelec, University Paris-Saclay, France

Hikmet Sari
Nanjing University of Posts and Telecommunications (NJUPT), China

Ejder Bastug
Nokia Bell Labs, France