Low-Complexity Robust Beamforming Design for IRS-Aided MISO Systems With Imperfect Channels

Omid, Yasaman; Shahabi, Seyyed MohammadMahdi; Pan, Cunhua; Deng, Yansha; Nallanathan, Arumugam

doi:10.1109/lcomm.2021.3049685

Cited by 41 publications

(40 citation statements)

References 12 publications

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“…As [17], [27]- [31], we assume the statistical CSI error model, which is applicable when the error is predominantly due to unavoidable inaccurate channel estimation in practical scenarios [27].…”

Section: A Channel Modelmentioning

confidence: 99%

“…The robust designs for IRS-assisted MISO communication system subjected to the rate outage probability constraints have been reported in [17], [27]- [29]. The authors in [30] and [31] proposed a pair of novel robust beamforming design schemes for the IRS-assisted MISO system, to minimize the mean squared error and to maximize the average sum-rate, respectively. It would like to mentioned that the above works [30], [31] adopted the stochastic method to address the CSI uncertainties by using the expected or the averaged performance, though it does not ensure the robust performance for each individual realization [22], [26].…”

Section: Introductionmentioning

confidence: 99%

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Robust Joint Design for Intelligent Reflecting Surfaces Assisted Cell-Free Networks

Xie¹,

He²,

Li³

et al. 2022

Preprint

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Intelligent reflecting surfaces (IRSs) have emerged as a promising economical solution to implement cell-free networks. However, the performance gains achieved by IRSs critically depend on smartly tuned passive beamforming based on the assumption that the accurate channel state information (CSI) knowledge is available at the central processing unit (CPU), which is practically impossible. Thus, in this paper, we investigate the impact of the CSI uncertainty on IRS-assisted cell-free networks. We adopt a stochastic method to cope with the CSI uncertainty by maximizing the expectation of the sum-rate, which guarantees the robust performance over the average. Accordingly, an average sum-rate maximization problem is formulated, which is non-convex and arduous to obtain its optimal solution due to the coupled variables and the expectation operation with respect to CSI uncertainties. As a compromising approach, we develop an efficient robust joint design algorithm with low-complexity. Particularly, the original problem is equivalently transformed into a tractable form by employing algebraic manipulations. Then, the locally optimal solution can be obtained iteratively. We further prove that the CSI uncertainty has no direct impact on the optimizing of the passive reflecting beamforming. It is worth noting that the investigated scenario is flexible and general in communications, thus the proposed algorithm can act as a general framework to solve various sum-rate maximization problems. Simulation results demonstrate that IRSs can achieve considerable data rate improvement for conventional cell-free networks, and confirm the resilience of the proposed algorithm against the CSI uncertainty.

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Section: A Channel Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Joint Design for Intelligent Reflecting Surfaces Assisted Cell-Free Networks

Xie¹,

He²,

Li³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…(d) Retraction operator: This step aims to map φt onto the manifold S M using the retraction operator θ t+1 = θt (5) Element-wise block coordinate descent (BCD) [106]- [109]: The idea of the element-wise BCD algorithm is simple. At the m-th iteration, one reflection coefficient θ m is optimized by keeping fixed the other reflecting coefficients θ m , m = m, m = 1, • • • , M .…”

Section: A Optimization Techniquesmentioning

confidence: 99%

An Overview of Signal Processing Techniques for RIS/IRS-aided Wireless Systems

Pan,

Zhou,

Zhi

et al. 2021

Preprint

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In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes. However, the improvements through applying such schemes operating at two endpoints (i.e., transmitter and receiver) only are limited even after five generations of wireless systems. Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) have emerged as a new and revolutionary technology that can configure the wireless environment in a favorable manner by properly tuning the phase shifts of a large number of quasi passive and low-cost reflecting elements, thus standing out as a promising candidate technology for the next-/sixth-generation (6G) wireless system. However, to reap the performance benefits promised by RIS/IRS, efficient signal processing techniques are crucial, for a variety of purposes such as channel estimation, transmission design, radio localization, and so on. In this paper, we provide a comprehensive overview of recent advances on RIS/IRS-aided wireless systems from the signal processing perspective. We also highlight promising research directions that are worthy of investigation in the future.

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“…The MISO broadcast system was also studied in [114], [127], [128], where the authors applied a different technique of Bernstein inequality to approximate the probabilistic outage constraints, which guarantees the non-outage performance of all users as well. Moreover, the authors in [129] applied the central limit theorem to the large-size IRS for deriving a deterministic lower bound on the achievable rate of each user in the presence of Gaussian CSI error. Then, the BS and IRS beamforming vectors are jointly optimized to maximize the sum of the lower-bounded rates of all users.…”

Section: A Irs Passive Beamforming Design With Imperfect Csimentioning

confidence: 99%

A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications

Zheng¹,

You²,

Mei³

et al. 2021

Preprint

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Intelligent reflecting surface (IRS) has emerged as a key enabling technology to realize smart and reconfigurable radio environment for wireless communications, by digitally controlling the signal reflection via a large number of passive reflecting elements in real time. Different from conventional wireless communication techniques that only adapt to but have no or limited control over dynamic wireless channels, IRS provides a new and cost-effective means to combat the wireless channel impairments in a proactive manner. However, despite its great potential, IRS faces new and unique challenges in its efficient integration into wireless communication systems, especially its channel estimation and passive beamforming design under various practical hardware constraints. In this paper, we provide a comprehensive survey on the up-to-date research in IRS-aided wireless communications, with an emphasis on the promising solutions to tackle practical design issues. Furthermore, we discuss new and emerging IRS architectures and applications as well as their practical design problems to motivate future research.

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Low-Complexity Robust Beamforming Design for IRS-Aided MISO Systems With Imperfect Channels

Cited by 41 publications

References 12 publications

Robust Joint Design for Intelligent Reflecting Surfaces Assisted Cell-Free Networks

Robust Joint Design for Intelligent Reflecting Surfaces Assisted Cell-Free Networks

An Overview of Signal Processing Techniques for RIS/IRS-aided Wireless Systems

A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications

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