Call for Papers

The unprecedented demands for high-quality and ubiquitous wireless services impose enormous challenges to existing cellular networks. To fulfil the diverse requirements, several latest technologies such as millimetre wave (mmWave) communications, ultra-dense networks (UDN), and massive multiple-input and multiple-output (MIMO) have been under consideration for the last several years. However, beyond 5G (B5G) systems aim to meet more stringent requirements to enable joint communications, sensing, localization, and computing services while ensuring ultra-high throughput, ultra-low latency, and ultra-high reliability for real-time communications. These requirements cannot be fully achieved with the existing technologies because of less ability to support different use cases.  Therefore, it is imperative to develop new and innovative technologies with low cost, complexity, and energy consumption.

To meet these stringent requirements, recently unmanned air vehicles (UAVs) are gaining in popularity because they play a significant role to overcome these challenges imposed by the energy-limited battery devices, random channel fluctuations, user mobility, and blocking effects. However, the UAV environment is a highly dynamic stochastic environment, so the conventional optimization approaches are not sufficient to address these challenges.  Hence, through Internet of UAVs (I-UAVs), cooperative UAVs can accomplish the sensing and transmission tasks as part of the B5G networks. However, I-UAV deployment poses several challenges such as interference among the UAVs connected to different base stations, requiring stronger computation power to fuse information from multiple UAVs. These challenges have severe effects to establish reliable and low latency communications because of the priority requirements. The I-UAVs environment is a highly dynamic stochastic environment, and consequently conventional optimization approaches are not sufficient to address these challenges. Artificial intelligence (AI) aided optimization approaches are helpful to cope with the dynamically fluctuating environment in I-UAV-aided networks.

Topics of interest for this Special Issue include but are not limited to:

• AI-driven novel architectures for I-UAV networks
• UAV-enabled simultaneous wireless information and power transfer (SWIPT) for I-UAV networks
• UAV-aided fog/edge computing for IoT networks
• RIS-assisted I-UAV networks for B5G communication
• Agile spectrum management for I-UAV networks
• Intelligent SDN control for I-UAV networks
• AI-driven joint trajectory and resource scheduling schemes for I-UAV networks
• Localization and swarm intelligence in I-UAV networks
• Blockchain Integrated solutions for AI-enabled I-UAV networks
• Low-complexity deep learning solutions for I-UAV trajectory/ beamforming optimization
• Joint optimization of RIS phase shifters and I-UAV placement
• Offloading Optimization in Edge AI for I-UAVs
• Distributed solutions for AI-enabled I-UAV networks
• Localization and swarm intelligence in I-UAV networks
• NOMA and interference management solutions for I-UAV networks
• Intelligent physical layer security solutions for I-UAV networks
• Experimental results for AI-enabled I-UAV networks

Submission Guidelines

Prospective authors should prepare their submissions in accordance with the rules specified in the Information for Authors of the IEEE Wireless Communications guidelines. Authors should submit a PDF version of their complete manuscript to Manuscript Central. Select ‘August 2022/ Artificial Intelligence Enabled Internet of UAVs Communications’ from the drop-down menu of Special Issues.

The timetable is as follows:

Important Dates

Manuscript Submission Deadline: 1 December 2021
Initial Decision Date: 1 Feburary 2022
Revised Manuscript Due: 1 March 2022
Final Decision Date: 1 April 2022
Final Manuscript Due: 15 June 2022
Publication Date: August 2022

Guest Editors

Zeeshan Kaleem
COMSATS University Islamabad, Pakistan

Sinem Coleri
Koc University, Turkey

Yansha Deng
King’s College London, UK

Chau Yuen
Singapore University of Technology and Design, Singapore

Mérouane Debbah
Technology Innovation Institute, Abu Dhabi, UAE