Special Issue "Cloud and Fog Radio Access Networks: Information, Communications, Inference and Learning Theoretic Views"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 30 November 2022 | Viewed by 546

Special Issue Editors

Prof. Dr. Shlomo Shamai (Shitz)
E-Mail Website
Guest Editor
The Viterbi Electrical and Computer Engineering Department, Technion - Israel Institute of Technology, Haifa, Israel
Interests: information theory and communications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Abdellatif Zaidi
E-Mail Website
Guest Editor
Institut Gaspard Monge, Université Paris-Est, 05 Boulevard Descartes, Cité Descartes, 77454 Champs sur Marne, France
Interests: network information theory; statistical decision theory; data compression; security and privacy
Dr. Iñaki Estella Aguerri
E-Mail Website
Guest Editor
Amazon, 08018 Barcelona, Spain
Interests: communication theory; information theory; wireless communication systems; joint source-channel coding; cooperative communications
Dr. Alon Kipnis
E-Mail Website
Guest Editor
Statistics Department, Stanford University, Mountain View, CA 94041, USA
Interests: mathematical statistics; information theory; signal processing; data compression

Special Issue Information

Cloud radio access networks (C-RAN) emerge as appealing architectures for next-generation wireless/cellular systems whereby the processing/decoding is migrated from the local base-stations/radio units (RUs) to one, or multiple, control/central units (CU) in the “cloud”. This is the basic network feature of future cell-less wireless technology. Fog radio access networks (F-RAN) address the case where the RUs are enhanced by having the ability of local caching of popular contents. This special issue is focused on the information-theoretic and communications aspects of such networks. 

Moreover, such frameworks of C-RAN, with oblivious signal processing at the RUs, have intimate connections on the theoretical and practical levels, to what is known as Distributed Information Bottleneck (IB) setting, and as such with basic network information theoretic frameworks such as: Remote Source-Coding, Information Combining, Chief-Executive-Officer (CEO) or Source Coding under Log-Loss, just to name a few. Evidently, learning, and distributed learning procedures will play a central role in future communications systems, and, as such, are important components also in C-RAN and F-RAN, let alone the fact that a variety of IB procedures are, stand alone, important tools in the mathematical analysis of learning methodologies (with focus on Deep Learning).

 This special issue of the Entropy journal is planned to focus on Information and Communications Theoretic aspects and views that are associated with the general framework of C-RAN, F-RAN, and IB. The outlook accounts also for multiple connections, both on the theoretical and practical levels, that emerge with distributed learning and estimation in this C-RAN, F-RAN framework, as well as, learning approaches for resource allocation and network optimization.

Prof. Dr. Shlomo Shamai (Shitz)
Prof. Dr. Abdellatif Zaidi
Dr. Iñaki Estella Aguerri
Dr. Alon Kipnis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • C-RAN
  • F-RAN
  • Information Bottleneck
  • Cell-less wireless networks
  • Federated learning
  • Distributed learning
  • Learning for resource allocation and network optimization

Published Papers

This special issue is now open for submission.
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