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Publication Date

Manuscript Submission Deadline

Feature Topic

Call for Papers

Traditional machine learning is centralized in the cloud (data centers). Recently, the security concern and the availability of abundant data and computation resources in wireless networks are pushing the deployment of learning algorithms towards the network edge. This has led to the emergence of a fast growing area, called edge learning, which integrates two originally decoupled areas: wireless communication and machine learning. It is widely expected that the advancements in edge learning would provide a platform for implementing edge artificial intelligence (AI) in 5G-and-Beyond systems and solving large-scale problems in our society ranging from autonomous driving to personalized healthcare. The repeated downloading and uploading of high-dimensional (millions to billions) model parameters (or their updates) by tens to hundreds of devices will place a heavy burden on the radio access networks. Overcoming the resultant communication bottleneck calls for designing new wireless techniques based on a communication-and-learning integration approach, forming the theme of this Feature Topic (FT). Specifically, this FT aims at introducing the major challenges and recent advancements in wireless communications for edge learning. Topics of interest include but are not limited to the following:

  • Computation-and-communication resource management for edge learning
  • Data compression for edge learning
  • Adaptive transmission for edge learning
  • Communication techniques for wireless crowd labelling
  • Ultra-low latency communications for edge learning and inference
  • Network architectures and protocols for edge learning
  • Experiments and testbeds on edge learning in wireless systems
  • Secure communications for edge learning

Important Dates

Manuscript Submission Deadline: 8 June 2020
Decision Notification: 1 September 2020
Final Manuscript Due: 15 October 2020
Publication Date: December 2020

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 “December 2020/Edge Learning” 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.

Guest Editors

Kaibin Huang
University of Hong Kong, Hong Kong

Mehdi Bennis
University of Oulu, Finland

Mérouane Debbah
Huawei France Research Center, France

Zhaohui Yang
King’s College London, UK