Channel Estimation for MIMO System Assisted by Intelligent Reflective Surface

Araújo, Gilderlan T. de; Pessoa, Lucas; Almeida, André L. F. de

doi:10.14209/sbrt.2020.1570661259

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…In the ideal case, the IRS reflecting units have a perfecting functioning, since practical amplitude and phase impairments are neglected [8]. The phase shifts have infinity resolution, which means that φ k can assume any value within the range (0, 2π) ∀k.…”

Section: A Idealized Irs Modelmentioning

confidence: 99%

See 1 more Smart Citation

IRS-Assisted Communications Under Practical Channel Estimation and Hardware Model

Pessoa¹,

Araújo²,

Gomes³

et al. 2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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In wireless communications, the propagation environment is not always favorable and may have several adverse conditions for data transmission and reception. The improper propagation conditions can be mitigated by the operator or by the current signal processing techniques. This classical paradigm can be rethought with the emerging concept of intelligent reflecting surface (IRS). IRS is a cost-effective, power-efficient and low hardware complexity solution capable of make wireless propagation environments more favorable by controlling in a software-defined way the amplitude and phase of the incident signal in order to improve the signal-to-noise ratio or mitigate interference at the intended receiver. However, in practice, the IRS operation are subject to inevitable impairments and practical issues, such as hardware limitations, blockages, and channel estimation errors that directly affects the system performance.In this paper, we study an IRS-assisted wireless communication system operating under one practical hardware model, which blockages at the IRS reflecting units are taken into account. Then, we investigate the impact of these real-world impairments on the system performance under practical channel estimation. The performance of an IRS-assisted communication under such practical constraints are evaluated in terms of the spectral efficiency (SE), normalized mean square error (NMSE) and symbol error rate (SER).

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Section: A Idealized Irs Modelmentioning

confidence: 99%

“…In [7], the authors consider an IRS operating under finite resolution of phase shifts, where the reflecting units can be tuned from a finite number of phases. In addition, the paper [8] have studied constraints on the amplitude response of the reflecting units. The authors in [9] have considered an IRS model under blockages.…”

Section: Introductionmentioning

confidence: 99%

IRS-Assisted Communications Under Practical Channel Estimation and Hardware Model

Pessoa¹,

Araújo²,

Gomes³

et al. 2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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“…Particularly, [29] capitalizes on the parallel factor (PARAFAC) decomposition to formulate an efficient iterative algorithm based on the alternating least squares (ALS) concept to solve the channel estimation problem in the downlink of a multi-user multiple input single output (MISO) network. Also, in [30] and [31], the authors develop simple iterative and closed-form channel estimation algorithms based on a PARAFAC modeling of the single-user MIMO scenario.…”

Section: Introductionmentioning

confidence: 99%

Channel Estimation in RIS-Assisted MIMO Systems Operating Under Imperfections

Gomes¹,

Araújo²,

Sokal³

et al. 2022

Preprint

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Reconfigurable intelligent surface (RIS) is a potential technology component of future wireless networks due to its capability of shaping the wireless environment. The promising gains of RIS-assisted multiple-input multiple-output (MIMO) systems in terms of extended coverage and enhanced capacity are, however, critically dependent on the accuracy of the channel state information. However, traditional channel estimation schemes are not applicable in RIS-assisted MIMO networks, since passive RISs typically lack the signal processing capabilities that are assumed by channel estimation algorithms. This becomes most problematic when physical imperfections or electronic impairments affect the RIS due to its exposition to different environmental effects or caused by hardware limitations from the circuitry. While these real-world effects are typically ignored in the literature, in this paper we propose efficient channel estimation schemes for RIS-assisted MIMO systems taking different imperfections into account. Specifically, we propose two sets of tensor-based algorithms, based on the parallel factor analysis decomposition schemes. First, by assuming a long-term model -in which the RIS imperfections, modeled as unknown phase shifts, are static within the channel coherence timewe formulate an iterative alternating least squares (ALS)-based algorithm for the joint estimation of the communication channels and the unknown phase deviations. Next, we develop the shortterm imperfection model, which allows both amplitude and phase RIS imperfections to be non-static with respect to the channel coherence time. We propose two iterative ALS-based and closed-form higher order singular value decomposition-based algorithms for the joint estimation of the channels and the unknown impairments. Moreover, we analyze the identifiability and computational complexity of the proposed algorithms and study the effects of various imperfections on the channel estimation quality. Simulation results demonstrate the effectiveness of the proposed tensor-based algorithms in terms of estimation accuracy and computational complexity.Index Terms-Alternating least squares (ALS), channel estimation, hardware impairments, higher-order singular value decomposition (HOSVD), imperfection detection, multiple input multiple output (MIMO), parallel factor analysis (PARAFAC), reconfigurable intelligent surface (RIS).

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A Survey on Optimal Channel Estimation Methods for RIS-Aided Communication Systems

Drampalou

Miridakis

Leligou

et al. 2023

Signals

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Next-generation wireless communications aim to utilize mmWave/subTHz bands. In this regime, signal propagation is vulnerable to interferences and path losses. To overcome this issue, a novel technology has been introduced, which is called reconfigurable intelligent surface (RIS). RISs control digitally the reflecting signals using many passive reflector arrays and implement a smart and modifiable radio environment for wireless communications. Nonetheless, channel estimation is the main problem of RIS-assisted systems because of their direct dependence on the system architecture design, the transmission channel configuration and methods used to compute channel state information (CSI) on a base station (BS) and RIS. In this paper, a concise survey on the up-to-date RIS-assisted wireless communications is provided and includes the massive multiple input-multiple output (mMIMO), multiple input-single output (MISO) and cell-free systems with an emphasis on effective algorithms computing CSI. In addition, we will present the effectiveness of the algorithms computing CSI for different communication systems and their techniques, and we will represent the most important ones.

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Channel Estimation for MIMO System Assisted by Intelligent Reflective Surface

Cited by 3 publications

References 11 publications

IRS-Assisted Communications Under Practical Channel Estimation and Hardware Model

IRS-Assisted Communications Under Practical Channel Estimation and Hardware Model

Channel Estimation in RIS-Assisted MIMO Systems Operating Under Imperfections

A Survey on Optimal Channel Estimation Methods for RIS-Aided Communication Systems

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