Call for Papers

While fifth-generation (5G) wireless networks are under deployment globally, both academia and industry have been enthusiastically exploring the roadmap for future sixth-generation (6G) wireless systems. Driven by the emergence of promising Internet-of-everything (IoE) applications ranging from extended reality and automated systems to the tactile Internet, 6G is expected to provide diverse services including e.g., communication, computing, and sensing, as well as achieve more ambitious network performance than 5G, such as global coverage and connectivity, ultra-high data rates, and extremely high reliability and low latency, which may not be fully achieved by existing technologies for 5G.  

To meet the future demands of 6G, an innovative concept referred to as smart radio environment has been recently proposed, which suggests that random and time-varying wireless channels can be dynamically controlled/reconfigured to enhance wireless communication performance, by leveraging digitally-controlled low-cost intelligent reflecting surface (IRS) or its various equivalents such as reconfigurable intelligent surface (RIS) and others. By dynamically tuning the signal reflection amplitude/phase, IRS enables a variety of key functions in wireless communication, such as creating effective line-of-sight (LoS) links, improving channel rank, reshaping channel realizations or their statistical distributions, and so on. Besides communication, IRS can also be exploited to improve the computing and sensing performance of future 6G wireless network. In particular, IRS passive beamforming can be leveraged to reconfigure the radio environment in favor of computation offloading as well as reshape the computation-load distribution over the network to achieve better usage of computational resources. Moreover, intelligent design of the IRS reflection coefficients can improve the efficiency and accuracy of radio-based sensing and localization in both indoor and outdoor environment, thus giving rise to a new solution approach for radio environment sensing.

This special issue aims to provide a forum for the most recent and promising research advances on the modelling, design, analysis, and implementation of IRS-aided wireless networks for achieving green communication, computing, and sensing, as well as provide new research directions in this emerging field. The topics of interest include, but are not limited to

• Energy-efficient coordination and resource allocation for IRS-aided wireless networks
• AI/ML techniques for green communication, computing, and sensing in IRS-aided networks
• Analytical, optimization and experimental approaches for green communication, computing, sensing in IRS-aided networks
• IRS deployment and energy management for sustainable IRS-aided networks
• Network architectures and protocols for IRS-aided communication, computing, and sensing
• System-level simulation, prototyping, and field-tests for IRS-aided green networks
• Fundamental efficiency limits of IRS-aided wireless networks
• Simultaneously transmitting and reflecting IRS aided communications
• Interplay between NOMA and IRS networks
• Resource allocation for IRS-aided Communications
• IRS-aided communication/computing powered by renewable energy
• Energy-efficient resource management for IRS-aided mobile edge computing systems
• IRS-aided green edge computing and edge learning
• IRS-aided spectrum sensing and green communication
• Energy-efficient radio-based sensing/localization in IRS-aided networks
• Integrated sensing and communication in IRS-aided networks
• Integration of IRS in massive MIMO, mm-Wave communications, THz communication, UAV communications, energy harvesting, fog/edge computing, federated learning, distributed computing/learning, spectrum sensing, aerial sensing, crowdsensing, etc.

Submission Guidelines

Authors need to follow the manuscript format and an allowable number of pages described at the IEEE TGCN Information for Authors page. To submit a manuscript for consideration for the special issue, please visit the journal submission website at Manuscript Central.

Important Dates

Manuscript Submission: 10 September 2021 24 September 2021
First Review Results: 10 November 2021
Second Review Results: 10 December 2021
Publication: March 2022 (Tentative)

Guest Editors