Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments

Zhou, Shaoqing; Xu, Wei; Wang, Kezhi; Renzo, Marco Di; Alouini, Mohamed‐Slim

doi:10.48550/arxiv.2004.09854

Cited by 1 publication

(4 citation statements)

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“…, where g(n) depends on the geometry of the RIS. Explicit expressions for a T and a RIS can be found in [12,Eq. (2)].…”

Section: A Channel Modelmentioning

confidence: 99%

“…I , σ 2 I . Remark 5: If the distribution of δ n is symmetric around zero, the non-central chi-square random variables in (12) and (13) are independent. This originates from Remark 3, and because the real and imaginary parts of Υ l,k and Ψ l converge, asymptotically (i.e., N 1), to Gaussian random variables.…”

Section: By Using the Notable Integralmentioning

confidence: 99%

“…For this reason, currently available analytical frameworks and scaling laws are only applicable to single-antenna transmitters and receivers. Representative contributions include [7]- [12]. In [7] and [8], in particular, the authors show that the average SNR at the receiver scales with the square of the number of tunable elements (N ) of the RIS.…”

Section: Introductionmentioning

confidence: 99%

“…In [10] and [11], the authors quantify the impact of phase noise for transmission over Rayleigh and Rician fading channels, respectively. In [12], the authors analyze the impact of phase noise and hardware impairments for transmission over line-of-sight (LOS) channels.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Beamforming Through Reconfigurable Intelligent Surfaces in Single-User MIMO Systems: SNR Distribution and Scaling Laws in the Presence of Channel Fading and Phase Noise

Xing-san¹,

Renzo

Liu³

et al. 2020

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We consider a fading channel in which a multiantenna transmitter communicates with a multi-antenna receiver through a reconfigurable intelligent surface (RIS) that is made of N reconfigurable passive scatterers impaired by phase noise. The beamforming vector at the transmitter, the combining vector at the receiver, and the phase shifts of the N scatterers are optimized in order to maximize the signal-to-noise-ratio (SNR) at the receiver. By assuming Rayleigh fading (or line-of-sight propagation) on the transmitter-RIS link and Rayleigh fading on the RIS-receiver link, we prove that the SNR is a random variable that is equivalent in distribution to the product of three (or two) independent random variables whose distributions are approximated by two (or one) gamma random variables and the sum of two scaled non-central chi-square random variables. The proposed analytical framework allows us to quantify the robustness of RIS-aided transmission to fading channels. For example, we prove that the amount of fading experienced on the transmitter-RIS-receiver channel linearly decreases with N . This proves that RISs of large size can be effectively employed to make fading less severe and wireless channels more reliable.

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“…, where g(n) depends on the geometry of the RIS. Explicit expressions for a T and a RIS can be found in [12,Eq. (2)].…”

Section: A Channel Modelmentioning

confidence: 99%

Section: By Using the Notable Integralmentioning

confidence: 99%