Artificial Intelligence (AI) catalyzes a paradigm shift that will change the way information and communication systems are designed and operated.

In the 5G era, network operation and management (O&M), resources and (micro-)services orchestration, performance and security improvement, and service diversity have reached an unprecedented level of complexity. Numerous communication service providers need to handle co-existing radio access technologies (2/3/4/5G), exploit more than 15 spectrum bands (from 400 MHz up to 52.6 GHz), configure more than 50 types of sites, and activate thousands of features with thousands of parameters to set. The performance of massive MIMO and heterogeneous networks affect more than 20 categories of devices and a large range of services, from voice over LTE and New Radio (NR) to AR/VR, air fiber, smart manufacturing, connected cars, smart buildings, smart energy, etc.

This complexity is calling for Autonomous Networks (AN). A scenario-oriented approach – specific to network planning and design (site design, survey, RF design, etc.), deployment (site verification, commissioning and integration, base station installation), O&M optimization (fault management, big event assurance, performance optimization), orchestration and new service provisioning – drives the shift from today’s partially automated networks, where decisions and service experience are still subject to human intervention, to highly and even fully autonomous networks by means of adaptive and self-learning policies and self-evolution.

This Feature Topic aims at presenting the most relevant scenarios, use-cases, prominent research outcomes, and state-of-the-art advances of autonomous mobile networks for 5G services and beyond.

Technical papers describing previously unpublished, original, state-of-the-art research, and not currently under review by a conference or a journal, will be considered. Specifically, this Feature Topic welcomes two categories of papers: 1) invited articles from qualified experts, and 2) contributed papers from the open call with a list of addressed topics.

We solicit articles on a variety of topics related to autonomous 5G networks and beyond. Topics of interest include, but are not limited to, the following:

- Architecture of autonomous mobile networks.
- Network embedding AI and representation learning.
- Cloud and edge AI, network AI and/or site AI solutions.
- Massive MIMO performance optimization.
- 3D visualization, traffic prediction and scenario recognition.
- Deep intelligent orchestration of resources and (micro-) services
- AI based alarm automation and troubleshooting.
- User experience improvement with multi parameter optimization.
- Deep intelligent energy saving in network domains and/or data centers.
- Wireless AI enabled positioning capability.
- Accurate network provisioning based on AI technology.
- AI security layered defense to evasion, poisoning, backdoor, model extraction, etc.
- Testbeds and experimentations of autonomous mobile networks.
- Simulation tools, methodologies, and performance evaluations of AN.
- New classes of AI for AN.

Submission Guidelines

Submitted papers should not be under consideration elsewhere for publication and manuscripts should conform to the standard format as indicated in the Information for Authors section of the Paper Submission Guidelines.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select “November 2020: AI for Mobile Networks” from the drop-down menu of Topic/Series titles.

Important Dates

* Manuscript Submission Deadline: 15 January 2020
* First Revisions/Reject Notification: 31 March 2020
* Revision Submission Deadline: 30 April 2020
* Final Notification of Acceptance/Reject: 31 July 2020
* Final Manuscript Due: 31 August 2020
* Publication Date: November 2020

Guest Editors
David Soldani (corresponding editor)
dr.david.soldani(AT)gmail.com
UNSW, Australia

Rahim Tafazolli
University of Surrey, UK

Emil Björnson
Linköping University, Sweden

Mehdi Bennis
University of Oulu, Finland

Sajal K. Das
Missouri University of Science and Technology, USA

Anthony C.K. Soong
Futurewei, USA

Antonio Manzalini
TIM, Italy