Periodically, we will organize Special Issues–proposals are always welcome. This is an opportunity to focus the content of an issue on a particular theme, which provides a unique coherence to the subject matter. Often, such Special Issues become valuable go-to resources for those working in the field and for those who want a convenient on-ramp to subjects in the field.

IEEE Journal on Miniaturization for Air and Space Systems Special Issue on Network Intelligence for Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are experiencing high growth rates and are utilized in a
wide array of applications such as remote sensing, surveillance, environmental monitoring, and
disaster management. Supporting such UAV-based applications necessitates advanced
communication and networking technologies for two main reasons. The applications requiring
computation-intensive data analysis pose a challenge to the limited battery life and on-board
computing capability of UAVs, which requires the support of remote servers via networks.
Besides, as UAV-based applications become complex, the requirements of timely data
transmission for each UAV and reliable communication for collaboration among UAVs are
increasingly strict.

With the recent advancements in artificial intelligence (AI), the sixth generation (6G)
networks are anticipated to incorporate various AI techniques natively, referred to as network
intelligence, providing new opportunities for UAV-based applications. By leveraging AI
techniques, network intelligence holds potential to facilitate automatically identifying the time-
varying demands of UAV-enabled applications and adaptively scheduling network resources
towards on-demand service provision. However, the highly dynamic network topologies, weakly
connected communication links, and various requirements of UAV-based applications challenge
the design of network intelligence. This special issue invites original and breakthrough research
in the field of network intelligence for UAVs. Topics include, but are not limited to, the
following:

Intelligent network architecture for UAVs
Intelligent network protocol designs for UAVs
Intelligent communication and networking technologies for UAVs
Intelligent UAV-assisted edge computing
Network intelligence for UAV-assisted sensing
Network intelligence for UAV deployment and trajectory design
Network intelligence for UAV navigation
AI-based network virtualization technologies, e.g., network slicing, for UAVs
AI-based network resource management for UAVs
AI-based UAV communication technologies, e.g., mmWave, Reconfigurable intelligent surfaces
Federated learning and distributed learning for UAVs
Distributed computing for UAVs
Tiny deep learning technologies for UAVs
Network digital twin for UAVs
Integrated sensing and communication related to UAVs
On-demand service provisioning with/for UAVs
Testing and evaluation tools of network intelligence for UAVs
Security and privacy issues of network intelligence for UAVs

Guest Editor:

Zan Li, Xidian University, zanli@xidian.edu.cn
Katsuya Suto, The University of Electro-Communications, k.suto@uec.ac.jp
Ling Lyu, Dalian Maritime University, linglyu@dlmu.edu.cn
Conghao Zhou, University of Waterloo, c89zhou@uwaterloo.ca
Nan Cheng, Xidian University, dr.nan.cheng@ieee.org
Wei Zhang, The University of New South Wales, w.zhang@unsw.edu.au

Timetable:

Manuscript Submission	Manuscript Review	Estimated Publication
February 1 – July 31, 2024	As received – Sep. 30, 2024	Q4 2024

Manuscript Submission:

Manuscripts with supporting documents are submitted to the web-based
portal: https://ieee.atyponrex.com/journal/jmass (select “Regular Paper” for “Article Type”).
Submission requirements include:

A Cover Letter clearly identifying the paper as a submission for the Special Issue. Any
changes to the author list between the original article and the new submission must be
explained with all co-authors (original, new, removed) as co-signers.
The manuscript.
The name of the Special Issue should be included in the upper right-hand corner of every
document submitted.
Additional details available on the manuscript submission
portal, https://ieee.atyponrex.com/journal/jmass and on J-MASS information
site, https://ieee.j-mass.org.