Abstract
Reconfigurable intelligent surface (RIS) for wireless networks has emerged as a promising future transmission technique to create smart radio environments that improve the system performance by turning the wireless channel into an adjustable system block. However, transceivers come with various hardware impairments, such as phase noise and in‐phase/quadrature‐phase imbalance (IQI). Hence, for robust configuration of RIS‐based communication under practical conditions, assuming the identical performance analysis when subject to IQI, will lead to inaccurate analysis. In this paper, the implementation of this novel transmission technique is thoroughly investigated under intensive realistic circumstances. For this purpose, based on the maximum likelihood (ML) detector, a novel analytical expression of average pairwise error probability under IQI is proposed and compared to the standard ML detector. Further, the proposed analytical approaches are confirmed by numerical simulations.
Highlights
Many attempts have been done in recent years to deliver new deployment models with high speeds, superior reliability, and negligible latency to meet the requirements of 5G standards
Motivated by the aforementioned limitations of the existing literature, this paper explores the design of an optimal Rx detector which is compared to the performance of the classical maximum likelihood (ML) in the presence of in-phase/quadrature-phase imbalance (IQI)
The average PEP (APEP) performance of the optimal and traditional ML detector for reconfigurable intelligent surface (RIS) under IQI based on the proposed analytic scenarios will be presented and proved with simulation results
Summary
Many attempts have been done in recent years to deliver new deployment models with high speeds, superior reliability, and negligible latency to meet the requirements of 5G standards To achieve these goals, several transmission techniques have been used such as millimeter wave (mmWave), orthogonal frequency division multiplexing (OFDM), and massive multiple input multiple output (MIMO) [1]. It is similar to other existing technologies, the RIS is based on a large number of thin passive reflectors without buffering and processing any incoming signals [4] These reflectors are designed based on two-dimensional meta-surfaces [12, 13]. For robust configuration, modeling the transceiver radio frequency (RF) front-end hardware as perfect will lead to inaccurate analysis [21] Both inphase (I) and quadrature (Q) modulator and demodulator at the Tx and Rx may introduce phase and/or amplitude mismatch [22]. Novel error probability analytical expressions are derived and proved with simulation results
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