An Efficient Calibration Algorithm for IRS-Aided mmWave Systems With Hardware Impairments

Zhang, Jiezhi; Zhong, Caijun; Zhang, Zhaoyang

doi:10.1109/lcomm.2021.3123808

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…By using ( 6), ( 8) and ( 10), Eq. ( 5) can be further simplified as (7) shown at the bottom of this page, where…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…Secondly, with given equalizer C and RIS reflecting matrix Θ, we optimize the procoder W. However, it is difficult to optimize W directly because the procoder W exists in the trace of Eq. (7) 15) is convex, and its optimal W opt can be obtained by resorting to the Karush-Kuhn-Tucker (KKT) conditions. Specifically, the Lagrangian function of Problem (15) is given by…”

Section: A Transceiver Optimizationmentioning

confidence: 99%

“…As a result, several researches have studied the impact of HIs at both the transceiver and the RIS in various RIS-aided scenarios. The authors in [7] investigated the joint calibration of the directionindependent and direction-dependent phase errors for an RISaided millimeter-wave system on the system performance. Besides, an RIS-aided MISO system was studied based on statistical channel state information (CSI) in [8] to maximize the system sum rate with the consideration of HIs at both transceiver and the RIS.…”

Section: Introductionmentioning

confidence: 99%

“…Besides, an RIS-aided MISO system was studied based on statistical channel state information (CSI) in [8] to maximize the system sum rate with the consideration of HIs at both transceiver and the RIS. However, in these contributions [7]- [9], users are equipped with single antenna and the impact of transceiver HIs and RIS phase noise on an RIS-aided MIMO system has not been investigated. Therefore, this work focuses on the downlink transmission of an RIS-aided single-user MIMO system, wherein there exists transceiver HIs and RIS phase noise.…”

Section: Introductionmentioning

confidence: 99%

“…has different forms in terms of the tiers of the 'diag' calculation, such as diag{WW H }, diag{Htdiag{WW H }H H t } and diag H H r Θdiag HtWW H H H t Θ H Hr . Then we derive two siginificant properties tr{Adiag{B}C H } = tr{Bdiag{C H A}} and tr{Adiag{Bdiag{C}B H}A H } = tr{Cdiag{B H diag{A H A}B}}.Based on these properties, we can optimize the optimization variable W in(7) by separating it from the diagonal transformation.…”

mentioning

confidence: 99%

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MSE-Based Transceiver Designs for RIS-Aided Communications With Hardware Impairments

et al. 2022

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It is challenging to precisely configure the phase shifts of the reflecting elements at the reconfigurable intelligent surface (RIS) due to inherent hardware impairments (HIs). In this paper, the mean square error (MSE) performance is investigated in an RIS-aided single-user multiple-input multipleoutput (MIMO) communication system with transceiver HIs and RIS phase noise. We aim to jointly optimize the transmit precoder, linear received equalizer, and RIS reflecting matrices to minimize the MSE. To tackle this problem, an iterative algorithm is proposed, wherein the beamforming matrices are alternately optimized. Specifically, for the beamforming optimization subproblem, we derive the closed-form expression of the optimal precoder and equalizer matrices. Then, for the phase shift optimization subproblem, an efficient algorithm based on the majorization-minimization (MM) method is proposed. Simulation results show that the proposed MSE-based RIS-aided transceiver scheme dramatically outperforms the conventional system algorithms that do not consider HIs at both the transceiver and the RIS.

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“…By using ( 6), ( 8) and ( 10), Eq. ( 5) can be further simplified as (7) shown at the bottom of this page, where…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Section: A Transceiver Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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MSE-Based Transceiver Designs for RIS-Aided Communications With Hardware Impairments

et al. 2022

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On the Optimal Discrete Phase Values of Reconfigurable Intelligent Surfaces

Cheng,

Wang,

Zhang

2024

Antennas Wirel. Propag. Lett.

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Reconfigurable Intelligent Sensing Surface Aided Wireless Powered Communication Networks: A Sensing-Then-Reflecting Approach

Luo,

Hu,

Xiang

et al. 2024

IEEE Trans. Commun.

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In this letter, we investigate the design of multiple reconfigurable intelligent sensing surfaces (RISSs) that enhance both communication and sensing tasks. An RISS incorporates additional active elements tailored to improve sensing accuracy. Our initial task involves optimizing placement of RISSs to mitigate signal interference. Subsequently, we establish power allocation schemes for sensing and communication within the system. Our final consideration involves examining how sensing results can be utilized to enhance communication, alongside an evaluation of communication performance under the impact of sensing inaccuracies. Numerical results reveal that the sensing task reaches its optimal performance with a finite number of RISSs, while the communication task exhibits enhanced performance with an increasing number of RISSs. Additionally, we identify an optimal communication spot under user movement.

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An Efficient Calibration Algorithm for IRS-Aided mmWave Systems With Hardware Impairments

Cited by 4 publications

References 17 publications

MSE-Based Transceiver Designs for RIS-Aided Communications With Hardware Impairments

MSE-Based Transceiver Designs for RIS-Aided Communications With Hardware Impairments

On the Optimal Discrete Phase Values of Reconfigurable Intelligent Surfaces

Reconfigurable Intelligent Sensing Surface Aided Wireless Powered Communication Networks: A Sensing-Then-Reflecting Approach

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