Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems With Hybrid Precoding

Niu, Hehao; Chu, Zheng; Zhou, Fuhui; Pan, Cunhua; Ng, Derrick Wing Kwan; Nguyen, Huan X.

doi:10.1109/tvt.2021.3131514

Cited by 56 publications

(38 citation statements)

References 41 publications

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“…Additionally, Ref. [37] investigated the joint passive BF and location optimization for secure data collection with a UAVcarried IRS, where a suboptimal solution for the secrecy rate maximization (SRM) problem was developed.…”

Section: Technical Literature Reviewmentioning

confidence: 99%

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Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Niu

Chu

Zhu

et al. 2022

Intell. and Converged Netw.

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This work investigates the potential of the aerial intelligent reflecting surface (AIRS) in secure communication, where an intelligent reflecting surface (IRS) carried by an unmanned aerial vehicle (UAV) is utilized to help the communication between the ground nodes. Specifically, we formulate the joint design of the AIRS's deployment and the phase shift to maximize the secrecy rate. To solve the non-convex objective, we develop an alternating optimization (AO) approach, where the phase shift optimization is solved by the Riemannian manifold optimization (RMO) method, while the deployment optimization is handled by the successive convex approximation (SCA) technique. Furthermore, to reduce the computational complexity of the RMO method, an element-wise block coordinate descent (EBCD) based method is employed. Simulation results verify the effect of AIRS in improving the communication security, as well as the importance of designing the deployment and phase shift properly.

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Section: Technical Literature Reviewmentioning

confidence: 99%

“…In fact, in Refs. [25,36,37], the authors proposed a deployment optimization method. However, these proposed methods assume the fading exponent of all these links is the same, which may not be practical.…”

Section: Deployment Optimizationmentioning

confidence: 99%

Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Niu

Chu

Zhu

et al. 2022

Intell. and Converged Netw.

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“…Higher rates (at the expense of an increased computational complexity) have been achieved by performing an alternating minimization (AltMin) of ∥F − AB∥ 2 F with respect to A and B, with A belonging to a complex circle manifold [2]. The optimization of A over the complex circle manifold, referred to as manifold optimisation (MO), has also been performed in the context of hybrid beamforming for scenarios involving intelligent reflective surfaces [9] and relay networks [10]. Other hybrid beamforming designs under the UM constraint avoid the complexity of manifold optimization by making use of a convexication of the optimization problem [4], [9], [11] or by heuristically applying phase extraction (PE) to determine A [2], [6], [7], [12]- [15].…”

Section: Introductionmentioning

confidence: 99%

“…The optimization of A over the complex circle manifold, referred to as manifold optimisation (MO), has also been performed in the context of hybrid beamforming for scenarios involving intelligent reflective surfaces [9] and relay networks [10]. Other hybrid beamforming designs under the UM constraint avoid the complexity of manifold optimization by making use of a convexication of the optimization problem [4], [9], [11] or by heuristically applying phase extraction (PE) to determine A [2], [6], [7], [12]- [15]. The rate resulting from AltMin manifold optimization in the case of SC modulation turns out to be close to the performance of the all-digital beamformer; therefore, the former rate has been considered as a performance benchmark for UM-constrained hybrid precoders [2].…”

Section: Introductionmentioning

confidence: 99%

Rate-Maximizing Zero-Forcing Hybrid Precoder for MU-MISO-OFDM

2023

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Hybrid precoders, consisting of an analog hardware-constrained part operating at radio frequency (RF) and a digital part operating at baseband, reduce the RF implementation complexity and power consumption of multi-antenna transceivers, at the expense of some rate loss compared to an all-digital precoder. The analog and digital parts of the hybrid precoder are commonly designed by performing a constrained matrix decomposition (MD) of the all-digital precoder, which aims to minimize the Euclidean distance between the matrices corresponding to the hybrid and the all-digital precoder. In contrast, in this contribution we determine the zero-forcing (ZF) hybrid precoder that directly maximizes the weighted sumrate of a MU-MISO-OFDM communication system, taking into account various hardware constraints on the analog part. The resulting maximum rate serves as a useful benchmark for comparison with other ZF hybrid precoders. In a multi-carrier massive MIMO scenario, the rate-maximizing ZF precoders show a considerable performance advantage over MD-type hybrid precoders, indicating that the latter precoders are far from optimum. This contribution also investigates the trade-off between performance and computational complexity. Because of the iterative nature of the rate-maximizing ZF hybrid precoders, their superior performance comes with a large computational complexity. When this complexity cannot be afforded, one should revert to the MD-type precoders, at the expense of a considerable performance penalty; among the MD-type precoders, the non-iterative ones have only a slightly worse performance but a significantly smaller computational complexity, in comparison with the iterative ones.

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“…The work in [21] jointly designed a hybrid precoder at the BS and the passive precoders at the IRSs to maximize the spectral efficiency. The authors in [22] investigated the use of double IRSs to improve the spectral efficiency in a multi-user MIMO network operating in the mmWave band. The work in [23] studied a double IRS assisted multiuser communication system with a cooperative passive beamforming design.…”

mentioning

confidence: 99%

Beamforming Design for the Performance Optimization of Intelligent Reflecting Surface Assisted Multicast MIMO Networks

Zhang¹,

Yang²,

Chen³

et al. 2022

Preprint

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In this paper, the problem of maximizing the sum of data rates of all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. In the considered model, one IRS is deployed to assist the communication from a multiantenna base station (BS) to the multi-antenna users that are clustered into several groups. Our goal is to maximize the sum rate of all users by jointly optimizing the transmit beamforming matrices of the BS, the receive beamforming matrices of the users, and the phase shifts of the IRS. To solve this non-convex problem, we first use a block diagonalization method to represent the beamforming matrices of the BS and the users by the phase shifts of the IRS. Then, substituting the expressions of the beamforming matrices of the BS and the users, the original sum-rate maximization problem can be transformed into a problem that only needs to optimize the phase shifts of the IRS. To solve the transformed problem, a manifold method is used. Simulation results show that the proposed scheme can S. Zhang and D. Liu are with the

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Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems With Hybrid Precoding

Abstract: Double intelligent reflecting surface-assisted multi-user MIMO mmWave systems with hybrid precoding. IEEE Transactions on Vehicular Technology .

Cited by 56 publications

References 41 publications

Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Rate-Maximizing Zero-Forcing Hybrid Precoder for MU-MISO-OFDM

Beamforming Design for the Performance Optimization of Intelligent Reflecting Surface Assisted Multicast MIMO Networks

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