A General Wideband Non-Stationary Stochastic Channel Model for Intelligent Reflecting Surface-Assisted MIMO Communications

Jiang, Hao; Ruan, Chengyao; Zhang, Zaichen; Dang, Jian; Wu, Liang; Mukherjee, Mithun; Costa, Daniel Benevides da

doi:10.1109/twc.2021.3066806

Cited by 62 publications

(39 citation statements)

References 32 publications

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“…In this figure, the channel between MT and IRS, IRS and MR, and MT and MR, are modeled as

H_{1}

H_{2}

, and

H_{3}

, respectively. The model presented in Figure 1A is a generalized model where by setting different parameter's values we can have different models presented in Reference 27–32 For example, if we consider

P = Q = 1

and

v_{MT} = v_{MR} = 0

the model will be the same as considered in Reference 27,32.…”

Section: Proposed Framework For Irs‐assisted Thz Communication Systemsmentioning

confidence: 99%

“…By comparing the discrete and continuous phase shifts, they concluded that the discrete phase shift does not change the absolute value of temporal auto correlation function. Taking mobility into account, the authors in Reference 30 proposed a wide‐band nonstationary wireless channel model for IRS‐assisted MIMO communication system. By utilizing 3‐D space, authors describe different types of IRS‐assisted wireless propagation environments.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent reflecting surface‐assisted terahertz communication towards B5G and 6G: State‐of‐the‐art

Raza

Ijaz

Ishfaq

et al. 2022

Micro & Optical Tech Letters

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After the deployment of 5th generation (5G), the beyond 5G (B5G) and 6th generation (6G) communication grabs the critical attention of academia and researchers. In ongoing cellular generation, the selected radio spectrum (i.e., millimeter waves [mm-Wave]) is unable to achieve the required data rates. Future cellular generations need more data rate and link reliability to serve emerging intelligent applications of B5G and 6G (e.g., autonomous driving, virtual reality, etc.). To handle these limitations of ongoing cellular generation, the researchers are working on key factors to have a smart, high capacity and ultra-reliable propagation environment. To increase the data rate of the B5G and 6G network systems, the terahertz (THz) band is selected. However, to increase link reliability, the intelligent reflecting surfaces (IRSs) have a crucial impact on wireless network environments. Immense work has been done on the performance analysis of IRS-assisted wireless communication networks. This treatise imposes a comparison of such IRS-assisted THz communication systems, and future promising applications.

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“…In this figure, the channel between MT and IRS, IRS and MR, and MT and MR, are modeled as

H_{1}

H_{2}

, and

H_{3}

P = Q = 1

and

v_{MT} = v_{MR} = 0

the model will be the same as considered in Reference 27,32.…”

Section: Proposed Framework For Irs‐assisted Thz Communication Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent reflecting surface‐assisted terahertz communication towards B5G and 6G: State‐of‐the‐art

Raza

Ijaz

Ishfaq

et al. 2022

Micro & Optical Tech Letters

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show abstract

“…While this study examines the non-stationary channels in which the receiver moves, the characteristic features of the scatterers in the environment are ignored, and analyses are merely conducted under sub-6 GHz frequency bands. Recently, the authors in [24] propose a general wideband non-stationary channel model for RIS-empowered communication systems operating at sub-6 GHz bands. By splitting the RIS-assisted MIMO channel model into subchannels, equivalent end-to-end channel models based on these subchannels are characterized under time-varying characteristics of MIMO systems in the presence of an RIS.…”

Section: A General Perspective On Ris Channel Modelingmentioning

confidence: 99%

Channel Modeling in RIS-Empowered Wireless Communications

Yıldırım¹,

Başar²

2022

Preprint

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One of the most critical aspects of enabling next-generation wireless technologies is developing an accurate and consistent channel model to be validated effectively with the help of real-world measurements. From this point of view, remarkable research has recently been conducted to model propagation channels involving the modification of the wireless propagation environment through the inclusion of reconfigurable intelligent surfaces (RISs). This study mainly aims to present a vision on channel modeling strategies for the RIS-empowered communications systems considering the state-of-the-art channel and propagation modeling efforts in the literature. Moreover, it is also desired to draw attention to open-source and standard-compliant physical channel modeling efforts to provide comprehensive insights regarding the practical use-cases of RISs in future wireless networks.

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“…Using a similar approach, the channel between the IRS and the Rx can be described as

\begin{matrix} true \\ right h_{2} = {[\begin{matrix} h_{11, R} & \dots & h_{m n, R} & \dots & h_{M N, R} \end{matrix}]}^{T} \in C^{P \times 1}, \end{matrix}

where

h_{m n, R}

represents the complex CIR of the propagation link between the unit cell

u_{m n}

and the Rx. Different from [20] in which only the NLOS propagation links were considered, here we incorporate both the LOS and NLOS links from

u_{m n}

to the Rx which is more realistic. Specifically, the complex CIR can be expressed as

\begin{matrix} true \\ right h_{m n, R} = h^{L} O S_{m n, R} + h^{N} L O S_{m n, R}, \end{matrix}

where

\begin{matrix} true \\ right h^{L} O S_{m n, R} = \sqrt{\frac{Ω_{2}}{{normalΩ}_{2} + 1}} e^{- j 2 π f_{c} ξ_{m n, R} / c} \times β^{L} O S_{m n, R}, \end{matrix}

where Ω 2 denotes the Rician factor of this subchannel,

ξ_{m n, R}

is the distance for the direct propagation link from the unit cell

u_{m n}

to the Rx, which can be expressed as

\begin{matrix} true \\ right ξ_{m n, R} = \sqrt{ξ_{I R S, R}^{2} + ξ_{m n}^{2} + 2<...>} \end{matrix}

…”

Section: Channel Modellingmentioning

confidence: 99%

“…Authors of [19] proposed a free space path loss model of the IRS-assisted wireless communication system based on the physical and electromagnetic characteristics of the IRS, which was a deterministic model and the statistical channel model is still desired. Recently, [20] employed a geometry-based stochastic channel model (GSCM) for IRS-assisted wireless communication system. The GSCM combines the statistical model with the deterministic model.…”

Section: Introductionmentioning

confidence: 99%

A geometry‐based stochastic channel model and its application for intelligent reflecting surface assisted wireless communication

et al. 2020

Self Cite

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Intelligent reflecting surface (IRS) is a new concept originating from metamaterials, which can achieve beamforming through controllable passive reflecting. This device makes it possible to engineer the wireless communication environment, and has drawn increasing attention. However, the associated channel models in current literature are mainly borrowed from conventional wireless channel models directly, omitting the unique features of IRS. In this paper, a geometry‐based stochastic channel model for IRS‐assisted wireless communication system is employed. The model has certain accuracy and low computational complexity. In particular, it captures the correlations of subchannels associated with different IRS elements, which is typically not considered in current works. Based on this channel model and the derived channel spatial correlation functions (CFs), an iterative reflection coefficients configuration method is proposed exploiting statistical channel state information to maximise the ergodic channel capacity. The impacts of the IRS spatial positions as well as the number of the IRS elements on the ergodic channel capacity is investigated through simulations. It is found that to obtain a larger ergodic channel capacity, the IRS should be placed in the vicinity of either the transmitter side or the receiver side, which is a useful guideline for practical deployment.

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A General Wideband Non-Stationary Stochastic Channel Model for Intelligent Reflecting Surface-Assisted MIMO Communications

Cited by 62 publications

References 32 publications

Intelligent reflecting surface‐assisted terahertz communication towards B5G and 6G: State‐of‐the‐art

Intelligent reflecting surface‐assisted terahertz communication towards B5G and 6G: State‐of‐the‐art

Channel Modeling in RIS-Empowered Wireless Communications

A geometry‐based stochastic channel model and its application for intelligent reflecting surface assisted wireless communication

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