Editorial:Special Topic on Reconfigurable Intelligent Surface(RIS)

Over the past two years,reconfigurable intelligent surface(RIS),as a promising emerging technology for Beyond 5 G(B5 G) and 6 G mobile communications systems,has attracted enormous interest from both academia and industry worldwide.In IMT-2030(6 G) Promotion Group of China,the RIS task force was created in June 2020.

Sparsity Modulation for 6G Communications

Sparsity modulation is a promising technology for the sixth generation(6G)of communication networks,which satisfies the high requirements in terms of spectral efficiency(SE)and energy efficiency(EE).Currently,many representative sparsity modulation schemes,such as spatial modulation,index modulation,media-based modulation,reconfigurable intelligent surface(RIS)-based/reflecting modulation,and subcarrier number modulation,have attracted the attention of the wireless research community.Different from conventional amplitude-phase modulation schemes,sparsity modulation employs one or more modulation dimension(s)in addition to the conventional amplitude-phase constellation,so as to form higher-dimensional modulation schemes,which considerably enhance the SE at a reduced implementation complexity under proper system configurations.It is worth noting that the modulation dimensions in current sparsity modulation schemes are not fully explored due to limited resources.

WIRELESS COMMUNICATIONS WITH RECONFIGURABLE INTELLIGENT SURFACES

With the commercialization of the fifth generattion(5G)of wireless networks in 2019,the development of the next generation of wireless standards is currently under discussion.To cope with the target 1000x improvement of system capacity,5G wireless standards have adopted massive MIMO as a key enabling physical layer technology to boost the spectral efficiency.

Effects of realistic reradiation models in digital reconfigurable intelligent surfaces

Reconfigurable intelligent surfaces(RISs)are a promising technology for wireless communication applications,but their performance is often optimized using simplified electromagnetic reradiation models.In this study,we explore the impact on the RIS performance of more realistic assumptions,including the(possibly imperfect)quantization of the reflection coefficients,subwavelength inter-element spacing,near-field location,and presence of electromagnetic interference.We find that design constraints can cause an RIS to reradiate power in unwanted directions.Therefore,it is important to optimize an RIS by considering the entire reradiation pattern.Overall,our study indicates that a 2-bit digitally controllable RIS with a nearly constant reflection amplitude and RIS elements with a size and inter-element spacing between(1/8)th and(1/4)th of the signal wavelength may offer a reasonable tradeoff between performance,complexity,and cost.

Editorial

Reconfigurable Intelligent Surface(RIS),also known as intelligent reflecting surface or large intelligent surface,is an emerging new physical-layer technology in the field of wireless communications.The basic idea of RIS is to deploy a reconfigurable passive array in the environment to manipulate the propagation of electron-magnetic waves.RIS promises a new design paradigm for wireless communications,where the wireless propagation environment can be dynamically controlled,which is substantially different from the conventional design that focuses only on the transmitter and receiver.For RIS-aided wireless communications,some of the current methodologies in conventional communication systems need to be revised,and some novel solutions are required to realize the potential benefits of the RIS.Although the number of publications about RIS has recently sharply increased,there are still many challenging issues to be extensively investigated,such as the RIS channel modeling,fundamental performance limits,the system design,joint optimization of the RIS and the transceivers,channel state information acquisition,and interdisciplinary applications.

Wireless communications empowered by reconfigurable intelligent surfaces: Model-based vs model-free channel estimation

Reconfigurable intelligent surfaces(RISs)are lately being attractive for their great potential in future sixth generation wireless communications(6G),which is attributed to their affordable energy consumption and easy integration.However,the large numbers of low-cost reflecting elements comprising RISs impose challenges for channel acquisition in various RIS-based wireless applications,such as RIS-enhanced orthogonal frequency-division multiplexing and multi-user multipleinput multiple-output systems.In this article,we first overview the state-of-the-art RIS hardware architectures designed to assist channel estimation for RIS-empowered wireless communication systems.We also overview existing channel estimation approaches,which are categorized into model-based and model-free techniques,and discuss their advantages and limitations depending on the RIS deployment.Design challenges with RIS-empowered systems in terms of hardware and other parameter limitations are presented,together with future research directions for channel estimation in RIS-based wireless systems,such as RISs with extremely large numbers of elements,multi-hop communications with RISs,and frequency division duplexing for high mobility systems.