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Publication Date

Manuscript Submission Deadline

Feature Topic

Call for Papers

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Extended Reality (XR) technologies will play a key role in the digital (r)evolution of modern societies, as they will enable services allowing humans to experience an immersive interaction with virtual, mixed, and augmented realities (VR, MR, and AR) in different societal contexts, including education, entertainment, transportation, manufacturing, and healthcare.

The XR ecosystem is growing at a rapid pace. XR devices, such as Head Mounted Devices (HMDs), Near Eye Displays (NEDs), Haptic Devices (HDs), and so on, are already hitting the market in order to enable humans to smoothly interact with different mixtures of physical and virtual worlds. However, high demands of XR services in terms of mobility, data rate, latency, and reliability puts stress on the communication infrastructure and therefore, enabling XR services is a key goal for next-generation communication systems, such as, beyond-5G (B5G) and 6G cellular networks. XR requires high-performing, flexible, scalable, and efficient systems that take advantage of Machine Learning (ML) and Artificial Intelligence (AI) tools for addressing complex end-to-end optimization, ultimately providing the expected Quality of Experience (QoE) to end users and satisfactory CAPEX/OPEX to service and technology providers.

Mobile communication systems enabling computation offloading to the edge/cloud/fog continuum, network slicing, function/service management and orchestration, and network/device energy efficiency are only a few examples of aspects that require further analysis in the XR context, as their enhancement is key toward further growth of the XR ecosystem. Therefore, research and industrial communities, as well as regulation and standardization fora, are increasing their efforts towards better defining XR use cases and requirements, and provide solutions to enable these services in modern communication systems.

This Feature Topic (FT) aims to bring together researchers and industry practitioners working on XR-related areas to share their ideas, findings, and results. Prospective authors are invited to submit articles on topics including, but not limited to:

  • XR traffic characteristics and connectivity requirements
  • B5G and 6G techniques, algorithms, and architectures for enabling XR services, e.g.,
    • Network architectures and deployment strategies, e.g., cloud/edge/fog computing, network slicing, XR service orchestration, management, and optimization
    • Core and Radio Access Network (RAN) optimization for supporting XR services, e.g., mechanisms for enhancing system capacity, such as user scheduling, resource allocation, mobility as well as mechanisms for enhancing power saving at both device and network side
    • Use of XR traffic knowledge to enable ML/AI-based approaches for the above aspects
  • Ongoing XR-related standardization activities (3GPP, ITU, ETSI, IEEE)
  • XR QoE: concepts, definitions, and validation in laboratory vs. crowdsourcing setups
  • XR experimental setups and measurements
  • XR use cases and business models

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-2304 / eXtended Reality” 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 Deadline: 30 November 2023
Decision Notification: 28 February 2024
Final Manuscript Due: 15 May 2024
Publication Date: June 2024

Guest Editors

Özgü Alay
University of Oslo, Norway

Frank Fitzek
TU Dresden, Germany

David Gomez-Barquero
Universitat Politecnica de Valencia, Spain

Jonas Kronander
Ericsson Research, Sweden