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Design, Control, Optimization, and Security of Next-Generation Communications Networks

This special issue belongs to the section “Microwave and Wireless Communications“.

Special Issue Information

Dear Colleagues,

To satisfy various business/industrial applications and extreme performance requirements based on Next-Generation Communication Networks (NGCNs) such as 6G, WiFi 8, and vehicular networks, the coordination of modeling, control, optimization, and security is needed to provide wide-area access to spatial information about the connected devices and surrounding environments. This scenario paves the way for pioneering innovative applications such as automation, aided driving, digital twins, industry 4.0, and integration with artificial intelligence, enhancing the perception and iteration of the physical environment.

The applications of NGCNs are difficult to implement without addressing the issues of implementing communication and networking models for more efficient communications between wireless devices and reliable data processing mechanisms that improve systems' control performances, especially when system resources are limited or subject to multiple hard/soft constraints such as system QoS, real-time response, and energy efficiency. Although it has attracted tremendous attention from academia and industry, many open questions remain to be explored.

The scope of this Special Issue is to present and highlight the advances in the latest optimization, control technologies, implementations, and applications of high-performance computation and communication for NGCNs. Consequently, the topics of interest include, but are not limited to, the following:

  • Design and new architectures for NGCNs;
  • Federated learning for NGCNs;
  • AI-based data analytics methods for NGCNs;
  • Distributed/decentralized control for NGCNs;
  • Energy transfer, harvesting, and saving in NGCNs;
  • Optimization of Resource Allocation and Management for NGCNs;
  • Security and Privacy Issues in NGCNs;
  • Green AI for training and inferencing;
  • Enabling machine learning over wireless networks;
  • Prototyping and testbeds for NGCN smart applications.

Dr. Lei Mo
Dr. Guiyun Liu
Guest Editors

Manuscript Submission Information

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Keywords

  • next-generation communication networks
  • system architecture
  • federated learning
  • data analysis
  • distributed/decentralized control
  • energy efficiency
  • resource allocation and management
  • security and Privacy
  • AI technology
  • machine learning

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Electronics - ISSN 2079-9292