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Register a new userA Path to Smart Radio Environments: An Industrial Viewpoint on Reconfigurable Intelligent Surfaces
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Added by
Ruiqi Liu
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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With both the standardization and commercialization completed in an unforeseen pace for the 5th generation (5G) wireless network, researchers, engineers and executives from the academia and the industry have turned their sights on candidate technologies to support the next generation wireless networks. Reconfigurable intelligent surfaces (RIS), sometimes referred to as intelligent reflecting surfaces (IRS), have been identified to be potential components of the future wireless networks because they can reconfigure the propagation environment for wireless signals with low-cost passive devices. In doing so, the coverage of a cell can be expected to increase significantly as well as the overall throughput of the network. RIS has not only become an attractive research area but also triggered a couple of projects to develop appropriate solutions to enable the set-up of hardware demonstrations and prototypes. In parallel, technical discussions and activities towards standardization already took off in some regions. Promoting RIS to be integrated into future commercial networks and become a commercial success requires significant standardization work taken place both at regional level standards developing organizations (SDO) and international SDOs such as the 3rd Generation Partnership Project (3GPP). While many research papers study how RIS can be used and optimized, few effort is devoted to analyzing the challenges to commercialize RIS and how RIS can be standardized. This paper intends to shed some light on RIS from an industrial viewpoint and provide a clear roadmap to make RIS industrially feasible.
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Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment smart. The typical use cases and applications for the smart environment include beyond 5G communication networks, smart cities, etc. The main advantage of employing RISs in such networks is a more efficient exploitation of spatial degrees of freedom. This advantage manifests in better interference mitigation as well as increased spectral and energy efficiency due to passive beam steering. Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering. Although the challenges for the design of communication networks, and specifically the Internet of Things (IoT), in such environments are known, there is no common enabler or solution for all these applications. Interestingly, the use of RISs in such scenarios can become such an enabler and a game changer technology. Surprisingly, the benefits of RIS for wireless networking in underwater and underground medium as well as in industrial and disaster environments have not been addressed yet. In this paper, we aim at filling this gap by discussing potential use cases, deployment strategies and design aspects for RIS devices in underwater IoT, underground IoT as well as Industry 4.0 and emergency networks. In addition, novel research challenges to be addressed in this context are described.
What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannons mathematical theory of communication with G. Greens and J. C. Maxwells mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.
Reconfigurable intelligent surfaces (RISs) are an emerging field of research in wireless communications. A fundamental component for analyzing and optimizing RIS-empowered wireless networks is the development of simple but sufficiently accurate models for the power scattered by an RIS. By leveraging the general scalar theory of diffraction and the Huygens-Fresnel principle, we introduce simple formulas for the electric field scattered by an RIS that is modeled as a sheet of electromagnetic material of negligible thickness. The proposed approach allows us to identify the conditions under which an RIS of finite size can or cannot be approximated as an anomalous mirror. Numerical results are illustrated to confirm the proposed approach.
Reconfigurable intelligent surfaces (RISs) provide an interface between the electromagnetic world of the wireless propagation environment and the digital world of information science. Simple yet sufficiently accurate path loss models for RISs are an important basis for theoretical analysis and optimization of RIS-assisted wireless communication systems. In this paper, we refine our previously proposed free-space path loss model for RISs to make it simpler, more applicable, and easier to use. In the proposed path loss model, the impact of the radiation patterns of the antennas and unit cells of the RIS is formulated in terms of an angle-dependent loss factor. The refined model gives more accurate estimates of the path loss of RISs comprised of unit cells with a deep sub-wavelength size. The free-space path loss model of the sub-channel provided by a single unit cell is also explicitly provided. In addition, two fabricated RISs, which are designed to operate in the millimeter-wave (mmWave) band, are utilized to carry out a measurement campaign in order to characterize and validate the proposed path loss model for RIS-assisted wireless communications. The measurement results corroborate the proposed analytical model. The proposed refined path loss model for RISs reveals that the reflecting capability of a single unit cell is proportional to its physical aperture and to an angle-dependent factor. In particular, the far-field beamforming gain provided by an RIS is mainly determined by the total area of the surface and by the angles of incidence and reflection.
Reconfigurable intelligent surface (RIS)-empowered communications is on the rise and is a promising technology envisioned to aid in 6G and beyond wireless communication networks. RISs can manipulate impinging waves through their electromagnetic elements enabling some sort of a control over the wireless channel. In this paper, the potential of RIS technology is explored to perform equalization over-the-air for frequency-selective channels whereas, equalization is generally conducted at either the transmitter or receiver in conventional communication systems. Specifically, with the aid of an RIS, the frequency-selective channel from the transmitter to the RIS is transformed to a frequency-flat channel through elimination of inter-symbol interference (ISI) components at the receiver. ISI is eliminated by adjusting the phases of impinging signals particularly to maximize the incoming signal of the strongest tap. First, a general end-to-end system model is provided and a continuous to discrete-time signal model is presented. Subsequently, a probabilistic analysis for the elimination of ISI terms is conducted and reinforced with computer simulations. Furthermore, a theoretical error probability analysis is performed along with computer simulations. It is demonstrated that with the proposed method, ISI can successfully be eliminated and the RIS-aided communication channel can be converted from frequency-selective to frequency-flat.
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