Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design

By Qurrat-Ul-Ain Nadeem, Abla Kammoun, Anas Chaaban, Merouane Debbah, Mohamed-Slim Alouini. IEEE Open Journal of the Communications Society, 2020

389 citations recorded by the source corpus.

The concept of reconfiguring wireless propagation environments using intelligent reflecting surfaces (IRS)s has recently emerged, where an IRS comprises of a large number of passive reflecting elements that can smartly reflect the impinging electromagnetic waves for performance enhancement. Previous works have shown promising gains assuming the availability of perfect channel state information (CSI) at the base station (BS) and the IRS, which is impractical due to the passive nature of the reflecting elements. This paper makes one of the preliminary contributions of studying an IRS-assisted multi-user multiple-input single-output (MISO) communication system under imperfect CSI. Different from the few recent works that develop least-squares (LS) estimates of the IRS-assisted channel vectors, we exploit the prior knowledge of the large-scale fading statistics at the BS to derive the Bayesian minimum mean squared error (MMSE) channel estimates under a protocol in which the IRS applies a set of optimal phase shifts vectors over multiple channel estimation sub-phases. The resulting mean squared error (MSE) is both analytically and numerically shown to be lower than that achieved by the LS estimates. Joint designs for the precoding and power allocation at the BS and reflect beamforming at the IRS are proposed to maximize the minimum user signal-to-interference-plus-noise ratio (SINR) subject to a transmit power constraint. Performance evaluation results illustrate the efficiency of the proposed system and study its susceptibility to channel estimation errors.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/8c9cae3541361b9367c583b55d2f4b32e9b59679

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

In Electrical and Electronic Engineering

In Ocean Engineering

Citations in the corpus

Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, methodology): “In existing literature, there are three main methods to estimate the CSI: • Brute-Force Method: In [3], a brute-force method is proposed, in which the CSI with respect to each RIS element is estimated sequentially by the AP while turning off other elements.”
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications (2020, background): “Channel Estimation (CE) in RIS-empowered multi-user communications is a challenging task since it involves the estimation of multiple channels simultaneously: the direct channels between the Base Station (BS) and each user, the channels between the RIS and BS, and the channels between the RIS and ea”
Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends (2022, background): “may result in imperfect CSIT due to limited channel training resources [194], [195].”
A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, methodology): “, apply the user-by-user successive channel estimation [86]– [88]), for which the received signal model in (4) reduces to”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, neutral): “For this scheme, the minimum number of sub-phases is equal to T = M + 1 [57].”
Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-User Communications: Achievable Rates With Limited Discrete Phase Shifts (2019, methodology): “A number of channel estimation methods can be found in [15], [16], which is out of the scope of this paper.”
Physics-Based Modeling and Scalable Optimization of Large Intelligent Reflecting Surfaces (2020, background): “[41], [42] for channel estimation schemes for IRS-assisted systems.”
Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds (2020, background): “Recently, smart radio environments (SREs) have been conceived as a new paradigm where the traditional radio environment is turned into a smart reconfigurable space that plays an active role in transferring and processing the information [1], [2].”
Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO (2019, methodology): “[15], [16] show that channel estimation in passive-RIS-assisted systems can be converted into a sequence of conventional MIMO channel estimation problems by turning on one RIS element at a time.”