A Framework of Robust Transmission Design for IRS-Aided MISO Communications With Imperfect Cascaded Channels

By Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Arumgam Nallanathan. IEEE Transactions on Signal Processing, 2020

527 citations recorded by the source corpus.

Intelligent reflection surface (IRS) has recently been recognized as a promising technique to enhance the performance of wireless systems due to its ability of reconfiguring the signal propagation environment. However, the perfect channel state information (CSI) is challenging to obtain at the base station (BS) due to the lack of radio frequency (RF) chains at the IRS. Since most of the existing channel estimation methods were developed to acquire the cascaded BS-IRS-user channels, this paper is the first work to study the robust beamforming based on the imperfect cascaded BS-IRS-user channels at the transmitter (CBIUT). Specifically, the transmit power minimization problems are formulated subject to the worst-case rate constraints under the bounded CSI error model, and the rate outage probability constraints under the statistical CSI error model, respectively. After approximating the worst-case rate constraints by using the S-procedure and the rate outage probability constraints by using the Bernstein-type inequality, the reformulated problems can be efficiently solved. Numerical results show that the negative impact of the CBIUT error on the system performance is greater than that of the direct CSI error.

Subfields: Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/480c7ce911bca6fd12545e6c5c23242668c4cfca

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Citations in the corpus

Reconfigurable Intelligent Surfaces for 6G Systems: Principles, Applications, and Research Directions (2021, unknown): “An initial attempt was devoted to a simple RIS-aided multiple-user downlink scenario in [13], and more emerging application scenarios are imperative to be investigated.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [157], the authors consider an RIS-aided multi-user MISO system and investigate the problem of robust beamforming under the assumption of imperfect knowledge of the cascaded channel from the base station to the users.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [158], the authors consider an RIS-aided multi-user MISO system and investigate the problem of robust beam-”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, unknown): “references [120]–[122], is omitted for brevity.”
A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, methodology): “MISO broadcast BS transmit power minimization constrained by the maximum outage probability for each user’s SINR Constrained stochastic SCA [130] Bernstein inequality and penalty-based AO [118] Bernstein inequality and AO with SDR [131], [132] Approximate user sum rate maximization Central limit the”
Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, methodology): “Developing low complexity channel estimation approaches [8], [89] and robust joint beamforming schemes [80], [82] constitute a”
Modeling and Architecture Design of Reconfigurable Intelligent Surfaces Using Scattering Parameter Network Analysis (2020, background): “In addition, research on optimizing RIS aided wireless systems with discrete phase shifts [25], [26], statistic and imperfect channel state information (CSI) [27], [28] and deep learning [29], [30] has also been conducted.”
Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, methodology): “With imperfect CSI, robust designs for RIS-aided communication systems were also studied [28], [29].”