Double-IRS Aided MIMO Communication Under LoS Channels: Capacity Maximization and Scaling

Han, Yitao; Zhang, Shuowen; Duan, Lingjie; Zhang, Rui

doi:10.1109/tcomm.2022.3151893

Cited by 62 publications

(26 citation statements)

References 28 publications

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“…where γ (3) (φ 1 , φ 2 ) is given by (16). Calculate φ † l,t according to (24), and set φ l,t = φ † l,t .…”

Section: A Optimization In General Rician Factor Regimementioning

confidence: 99%

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Analysis and Optimization of A Double-IRS Cooperatively Assisted System with A Quasi-Static Phase Shift Design

Ding¹,

Feng²,

Ding³

et al. 2022

Preprint

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The analysis and optimization of single intelligent reflecting surface (IRS)-assisted systems have been extensively studied, whereas little is known regarding multiple-IRS-assisted systems. This paper investigates the analysis and optimization of a double-IRS cooperatively assisted downlink system, where a multi-antenna base station (BS) serves a single-antenna user with the help of two multi-element IRSs, connected by an inter-IRS channel. The channel between any two nodes is modeled with Rician fading.The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, and the two IRSs adopt a cooperative quasi-static phase shift design. The goal is to maximize the average achievable rate, which can be reflected by the average channel power of the equivalent channel between the BS and user, at a low phase adjustment cost and computational complexity. First, we obtain tractable expressions of the average channel power of the equivalent channel in the general Rician factor, pure line of sight (LoS), and pure non-line of sight (NLoS) regimes, respectively. Then, we jointly optimize the phase shifts of the two IRSs to maximize the average channel power of the equivalent channel in these regimes. The optimization problems are challenging non-convex problems. We obtain globally optimal closed-form solutions for some cases and propose computationally efficient iterative algorithms to obtain stationary points for the other cases. Next, we compare the computational complexity for optimizing the phase shifts and the optimal average channel power of the double-IRS cooperatively assisted system with those of a counterpart single-IRS-assisted system at a large number of reflecting elements in the three regimes. Finally, we numerically demonstrate notable gains of the proposed solutions over the existing solutions at different system parameters. To our knowledge, this is the first work that optimizes the quasi-static phase shift design of a double-IRS cooperatively assisted system and characterizes its advantage over the optimal quasi-static phase shift design of the counterpart single-IRS-assisted system.

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“…where γ (3) (φ 1 , φ 2 ) is given by (16). Calculate φ † l,t according to (24), and set φ l,t = φ † l,t .…”

Section: A Optimization In General Rician Factor Regimementioning

confidence: 99%

“…the total number of reflecting elements of a double-IRS-assisted system is higher in order than that of the counterpart single-IRS-assisted system. In [23]- [25], the authors optimize the BS beamformer and IRS phase shifts to maximize the signal-to-interference-plus-noise ratio (SINR) [23], capacity [24], and secrecy rate [25].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of A Double-IRS Cooperatively Assisted System with A Quasi-Static Phase Shift Design

Ding¹,

Feng²,

Ding³

et al. 2022

Preprint

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“…Assuming the quadrature phase shift keying (QPSK) is employed as the modulation scheme, according to ( 7), (16), and (19), the BERs at Bob with no PL, PL, and APL are given by…”

Section: Performance Loss Of Ber At Bobmentioning

confidence: 99%

“…The problem of joint active and passive beamforming optimization for an IRS-aided downlink multi-user multipleinput multiple-output (MIMO) system was investigated in [18], where a vector approximate message passing algorithm was proposed to optimize the IRS phase shifts. In [19], the transmit covariance matrix and passive beamforming matrices of the two cooperative IRSs were jointly optimized to maximize rate, and a novel low-complexity alternating optimization algorithm was presented.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Wireless Network Aided by Discrete-Phase-Shifter IRS

Rongen¹,

Yin²,

Sun³

et al. 2022

Preprint

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Discrete phase shifters of intelligent reflecting surface (IRS) generates phase quantization error (QE) and degrades the receive performance at the receiver. To make an analysis of the performance loss caused by IRS with phase QE, based on the law of large numbers, the closed-form expressions of signal-tonoise ratio (SNR) performance loss (PL), achievable rate (AR), and bit error rate (BER) are successively derived under line-ofsight (LoS) channels and Rayleigh channels. Moreover, based on the Taylor series expansion, the approximate simple closed form of PL of IRS with approximate QE is also given. The simulation results show that the performance losses of SNR and AR decrease as the number of quantization bits increase, while they gradually increase with the number of IRS phase shifter elements increase. Regardless of LoS channels or Rayleigh channels, when the number of quantization bits is larger than or equal to 3, the performance losses of SNR and AR are less than 0.23dB and 0.08bits/s/Hz, respectively, and the BER performance degradation is trivial. In particular, the performance loss difference between IRS with QE and IRS with approximate QE is negligible when the number of quantization bits is not less than 2.

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“…By adjusting its phase shift matrix, IRS may intelligently control and change wireless environment to improve system spectral efficiency and energy efficiency [24]- [28]. IRS can be applied to a diverse variety of communication areas, such as MIMO [29], [30], relay [31], secure wireless information and power transmission (SWIPT) [32], spatial modulation networks [33] and unmanned aerial vehicle (UAV) network [34]. In [30], adjusting the phase of IRS was to mitigate the interference at cell-edge, and the performance of cell-edge user was improved.…”

Section: Introductionmentioning

confidence: 99%

Two Low-complexity Efficient Beamformers for IRS-aided Directional Modulation Networks

Yang¹,

Rongen²,

Chen³

et al. 2022

Preprint

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As an excellent tool for aiding communication, intelligent reflecting surface (IRS) can extend the coverage area, remove blind area, and achieve a dramatic rate improvement. In this paper, we improve the secret rate (SR) performance at directional modulation (DM) networks using IRS. To fully explore the benefits of IRS, two efficient methods are proposed to enhance SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS phase shift matrix, which is called Max-SR-SLNR. Here, Eve is maximally interfered by transmitting artificial noise (AN) along the direct path and null-space projection (NSP) on the remaining two channels. To reduce the computational complexity, the CM, AN beamforming and IRS phase shift design are independently designed in the following methods. The CM beamforming vector is constructed based on maximum ratio transmission (MRT) criteria along the channel from Alice-to-IRS, and phase shift matrix of IRS is directly given by phase alignment (PA) method. This method is called MRT-NSP-PA. Simulation results show that the SR performance of the Max-SR-SLNR method outperforms the MRT-NSP-PA method in the cases of small-scale and medium-scale IRSs, and the latter approaches the former as IRS tends to lager-scale.

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Double-IRS Aided MIMO Communication Under LoS Channels: Capacity Maximization and Scaling

Cited by 62 publications

References 28 publications

Analysis and Optimization of A Double-IRS Cooperatively Assisted System with A Quasi-Static Phase Shift Design

Analysis and Optimization of A Double-IRS Cooperatively Assisted System with A Quasi-Static Phase Shift Design

Performance Analysis of Wireless Network Aided by Discrete-Phase-Shifter IRS

Two Low-complexity Efficient Beamformers for IRS-aided Directional Modulation Networks

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