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The sixth generation (6G) wireless networks are envisioned to provide intelligent, deep, and ubiquitous connectivity integrating communication, sensing, localization, and computing functionalities for a diverse group of consumers and industries. While research efforts focus on evolving key fifth generation (5G) technologies to meet this goal, the resulting solutions, like ultra-massive/holographic multiple-input multiple-output (MIMO) and terahertz (THz) communication incur high power consumption and hardware costs, and face signal attenuation and blockages. This gives rise to the need for investigating integrated communication, sensing, localization, and computing solutions with intelligent yet energy-and-hardware-efficient techniques. Recently, reconfigurable metasurfaces have emerged as a key enabler of this vision and have found important applications in 6G as reconfigurable intelligent surfaces (RISs) and reconfigurable holographic surfaces (RHSs). Capable of simultaneously reflecting and/or refracting the incident signals via flexible phase shift reconfiguration, the RHSs can actively generate beams in desired directions through wave-based beamforming, while RISs can passively shape wireless propagation environments into a desirable form, in a cost-and energy-efficient manner. 

Given their enormous potential to meet different performance objectives in an energy-and-cost-efficient manner, the use of multi-function RISs/RHSs should be explored to enable integrated communication, sensing, localization, and/or computing functionalities by fully or partially sharing the same hardware, spectrum, waveform, and wireless resources. Specifically, integrated sensing and communication (ISAC) can be enabled by shaping the ISAC signals across the RIS/RHS, and by utilizing intelligent omni-surfaces with sensing capabilities. RISs/RHSs can also support mobile edge computing in an ISAC framework by controlling the interference between communication, sensing, and computation offloading. Artificial Intelligence (AI) and Machine Learning (ML) are gaining attention in the design of multi-function RISs/RHSs systems and can play an important role in reducing the overhead or speeding up the algorithmic processing required for channel estimation, beamforming design, and resource management. Furthermore, energy-efficient multi-function RIS/RHS configurations can be applied across the radio spectrum, from sub-6 GHz to millimeter wave (mmWave) to THz frequencies. Multi-function RISs/RHSs can be also intertwined with emerging technologies, such as Internet of Things (IoT), Internet of Everything (IoE), Internet of Intelligent Things (IoIT), Internet of Space Things (IoST), Vehicle to Everything (V2X), and Unmanned Aerial Vehicles (UAVs). The development of multi-function RIS/RHS configurations also requires advanced signal processing methods for designing transmit waveforms and precoders, processing received signals, estimating channels, beam tracking, and allocating resources, which has been the focus of several ongoing research efforts.

Motivated by the role of RISs/RHSs in the field of future 6G Wireless, this Special Issue (SI) seeks to assemble cross-cutting and high-quality original tutorial style research articles in the following areas incorporated with multi-function RISs/RHSs Empowered 6G Networks:

  • Integrated sensing and communication, integrated sensing and localization, integrated communication and computing, and integrated communication, sensing, and computing.
  • Intelligent omni-surfaces with sensing capabilities. 
  • Use-cases and real-world applications.
  • AI and ML.
  • Standardization progress, experimental demonstrations, and prototypes.
  • Ethical considerations, such as the privacy of users’ data, digital divide, and environmental footprint of 6G infrastructure.
  • Network architectures and transmission protocols design.
  • Waveform design, channel estimation, and beamforming.
  • Next generation multiple access schemes.
  • Electromagnetic wave compliant modeling and design.
  • Integrated space-air-ground networks, IoT, IoE, IoIT, IoST, V2X, and UAV-assisted wireless.
  • Cell-free wireless, full-duplex, mmWave, and THz systems.
  • Mobile edge computing and distributed and cloud computing.
  • Estimation theory and advanced signal processing.

Submission Guidelines

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 the magazine’s Manuscript Central submission site. Select “November2024/RISfor6G” from the drop-down menu of Topic titles.

Important Dates

Manuscript Submission Deadline: 20 May 2024
Initial Decision Notification: 20 July 2024
Revised Manuscript Due: 20 August 2024
Final Decision Notification: 20 September 2024
Final Manuscript Due: 30 September 2024
Publication Date: November 2024

Guest Editors

Qurrat-Ul-Ain Nadeem
New York University Abu Dhabi, UAE

Aryan Kaushik
University of Sussex, UK

Marco Di Renzo
Paris-Saclay University, France

Octavia A. Dobre
Memorial University of Newfoundland, Canada

A Lee Swindlehurst
University of California Irvine, USA

Miguel Dajer
Futurewei Technologies, USA

Doowhan Lee
NTT Corporation, Japan