Article

Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement

Abstract and Figures

Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this paper, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying the physics and electromagnetic nature of RISs. The proposed models, which are first validated through extensive simulation results, reveal the relationships between the free-space path loss of RIS-assisted wireless communications and the distances from the transmitter/receiver to the RIS, the size of the RIS, the near-field/far-field effects of the RIS, and the radiation patterns of antennas and unit cells. In addition, three fabricated RISs (metasurfaces) are utilized to further corroborate the theoretical findings through experimental measurements conducted in a microwave anechoic chamber. The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.
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... Ref. [20] uses the Huygens-Fresnel principle to study the wireless channel of reflective RIS and gives a closed expression for calculating the received power of RISs. Ref. [21] verifies the proposed RIS free space path loss model experimentally, and the measurement results show that the established model has strong credibility. Considering the influence of RIS panel size and terminal mobility on RIS channel characteristics, an RIS geometric randomness channel model in three-dimensional (3D) space is established in [22]. ...
... Consistent with the analysis in [21], we use L Tx p,q , θ Tx p,q , and ϕ Tx p,q , respectively, to denote the distance, elevation angle, and azimuth angle from the base station to the RIS reflection unit (p, q). Similarly, the corresponding parameters from the UE to the RIS reflection unit (p, q) are represented by L Rx p,q , θ Rx p,q , and ϕ Rx p,q , respectively. ...
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Terahertz communication has been proposed as one of the basic key technologies of the sixth-generation wireless network (6G) due to its significant advantages, such as ultra-large bandwidth, ultra-high transmission rates, high-precision positioning, and high-resolution perception. In terahertz-enabled 6G communication systems, the intelligent reconfiguration of wireless propagation environments by deploying reconfigurable intelligent surfaces (RIS) will be an important research direction. This paper analyzes the far field and near field of RIS-assisted wireless communication and a detailed system description is presented. Subsequently, this paper presents a specific study of the channel model for an RIS-assisted 6G communication system in the far-field and near-field cases, respectively. Finally, an integrated simulation of the channel models for the far-field and near-field cases is carried out, and the performance of the RIS auxiliary link measured in terms of signal-to-noise ratio (SNR) is compared and analyzed. The results show that increasing the size of the RIS surface to improve the SNR is an effective method to enhance the coverage performance of the 6G THz communication system under the strong guarantee of the ultra-large bandwidth of THz.
... On account of the previously described advantages, RISs are in fact gaining a lot of momentum in massive access scenarios [52,[59][60][61][62][63][64][65][66][67][68][69][70][71][72][73] because of their aforementioned ability to turn the stochastic nature of the wireless environment into a programmable channel. RISs have been recently proposed for a variety of applications including secure communications [67,68], nonorthogonal multiple access [69], over-the-air-computation [70], or energy-efficient cellular networks [71,72]. ...
... The receive power thus scales as the inverse of the product of the distance of the individual paths from the BS to the RIS and from the RIS to the UE. Additionally, it scales as the square of the number of the RIS reflecting elements L (in accordance with recent works on pathloss modelling [55,57,63,64]). Hence, by increasing the number of RIS antenna elements, we can counteract the decrease in receive power due to the distance of the combined path from the BS to RIS and from the RIS to the UE. This notably suggests that RISs can be used smartly to effectively increase the coverage area of wireless networks. ...
Thesis
The exponential increase of wireless user equipments (UEs) and network services associated with current 5G deployments poses several unprecedented design challenges that need to be addressed with the advent of future beyond-5G networks and novel signal processing and transmission schemes. In this regard, massive MIMO is a well-established access technology, which allows to serve many tens of UEs using the same time-frequency resources. However, massive MIMO exhibits scalability issues in massive access scenarios where the UE population is composed of a large number of heterogeneous devices. In this thesis, we propose novel scalable multiple antenna methods for performance enhancement in several scenarios of interest. Specifically, we describe the fundamental role played by statistical channel state information (CSI) that can be leveraged for reduction of both complexity and overhead for CSI acquisition, and for multiuser interference suppression. Moreover, we exploit device-to-device communications to overcome the fundamental bottleneck of conventional multicasting. Lastly, in the context of millimiter wave communications, we explore the benefits of the recently proposed reconfigurable intelligent surfaces (RISs). Thanks to their inherently passive structure, RISs allow to control the propagation environment and effectively counteract propagation losses and substantially increase the network performance.
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