Simultaneously Transmitting and Reflecting (STAR) Intelligent Omni-Surfaces, Their Modeling and Implementation

Xu, Jiaqi; Liu, Yuanwei; Mu, Xidong; Zhou, Joey Tianyi; Song, Lingyang; Poor, H. Vincent; Hanzo, Lajos

doi:10.48550/arxiv.2108.06233

Cited by 6 publications

(12 citation statements)

References 16 publications

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“…For (8), by exploiting (1)-( 5), it can be shown that the complex-valued T&R coefficients of the passive STAR-RIS elements have to satisfy…”

Section: B Correlated Tandr Phase-shift Modelmentioning

confidence: 99%

“…To investigate the impact of the proposed correlated T&R phase-shift model given in (8) on wireless system performance, we consider a STAR-RIS-aided two-user downlink system, as illustrated in Fig. 3.…”

Section: System Modelmentioning

confidence: 99%

“…In this section, we propose three STAR-RIS PSC strategies for the proposed correlated phaseshift model in (8). We note that due to the T&R phase-shift correlation in (8), existing results on phase-shift optimization for conventional RISs and STAR-RISs with independent phase shifts are not applicable for the considered passive STAR-RISs.…”

Section: Practical Phase-shift Configuration Strategies For Star-rissmentioning

confidence: 99%

“…Without loss of generality, assume that user R is the primary user. In the first step, the phase terms {φ R 1 , • • • , φ R M } are configured to maximize the channel gain of user R without considering the phase-shift correlation constraint in (8). This yields the following optimization problem:…”

Section: A Primary-secondary Phase-shift Configuration (Ps-psc) Strategymentioning

confidence: 99%

“…To facilitate this, each STAR-RIS element has to dynamically impose two distinct tunable phase-shift values, one for the transmitted signal and one for the reflected signal [4]. Given the above unique features, STAR-RISs have been regarded as a promising technology for future wireless networks, thus attracting extensive interest from both industry [6][7][8] and academia [4,9,10].…”

Section: Introductionmentioning

confidence: 99%

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STAR-RISs: A Correlated T&R Phase-Shift Model and Practical Phase-Shift Configuration Strategies

Xu,

Liu,

et al. 2021

Preprint

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A correlated transmission and reflection (T&R) phase-shift model is proposed for passive lossless simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). A STAR-RIS-aided two-user downlink communication system is investigated for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA). To evaluate the impact of the correlated T&R phase-shift model on the communication performance, three phase-shift configuration strategies are developed, namely the primary-secondary phase-shift configuration (PS-PSC), the diversity preserving phase-shift configuration (DP-PSC), and the T/R-group phase-shift configuration (TR-PSC) strategies.Furthermore, we derive the outage probabilities for the three proposed phase-shift configuration strategies as well as for those of the random phase-shift configuration and the independent phase-shift model, which constitute performance lower and upper bounds, respectively. Then, the diversity order of each strategy is investigated based on the obtained analytical results. It is shown that the proposed DP-PSC strategy achieves full diversity order simultaneously for users located on both sides of the STAR-RIS.Moreover, power scaling laws are derived for the three proposed strategies and for the random phaseshift configuration. Numerical simulations reveal a performance gain if the users on both sides of the STAR-RIS are served by NOMA instead of OMA. Moreover, it is shown that the proposed DP-PSC J. Xu and Y. Liu are with the

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“…For (8), by exploiting (1)-( 5), it can be shown that the complex-valued T&R coefficients of the passive STAR-RIS elements have to satisfy…”

Section: B Correlated Tandr Phase-shift Modelmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Section: Practical Phase-shift Configuration Strategies For Star-rissmentioning

confidence: 99%

Section: A Primary-secondary Phase-shift Configuration (Ps-psc) Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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STAR-RISs: A Correlated T&R Phase-Shift Model and Practical Phase-Shift Configuration Strategies

Xu,

Liu,

et al. 2021

Preprint

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Intelligent Omni-Surfaces (IOSs) for the MIMO Broadcast Channel

Mohamed

Perović

Renzo

2022

2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)

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In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves. We focus our attention on the multiple-input multiple-output (MIMO) broadcast channel, and we introduce an algorithm for jointly optimizing the covariance matrix at the base station, the matrix of reflection and transmission coefficients at the IOS, and the amount of power that is reflected and refracted from the IOS. The distinguishable feature of this work lies in taking into account that the reflection and transmission coefficients of an IOS are tightly coupled. Simulation results are illustrated to show the convergence of the proposed algorithm and the benefits of using surfaces with simultaneous reflection and refraction capabilities.

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Rate-Splitting Multiple Access and Dynamic User Clustering for Sum-Rate Maximization in Multiple RISs-Aided Uplink mmWave System

Katwe

Singh

Clerckx

et al. 2022

IEEE Trans. Commun.

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In this paper, a reconfigurable intelligent surfaces (RISs)-aided millimeter wave (mmWave) uplink (UL) rate-splitting multiple access (RSMA) system is investigated which targets to achieve better rate performance and enhanced coverage capability for multiple users. The considered UL RSMA model splits the rate for each user by dividing their message into multiple parts and hence exploits all the necessary degrees of freedom to achieve maximum capacity region and high user fairness. In particular, we focus on the sum-rate maximization for considered UL RSMA system subject to joint optimization of power allocation to the UL users and beamforming design, i.e., active receive beamforming at the base-station (BS) and passive beamforming at multiple RISs. To efficiently mitigate high inter-node interference in multi-user scenario, we first provided a low-complex user pairing scheme based on k-means clustering and then develop an effective low-cost alternating optimization framework to solve the joint optimization problem sub-optimally by decoupling the problem into different sub-problems of power allocation and beamforming design. Specifically, the sub-problems of power allocation and beamforming design are solved using successive convex approximation, Riemannian manifold and fractional programming techniques. Later, the unified solution based on block coordinate descent (BCD) algorithm is proposed. Extensive numerical simulations validate that the user-clustering effectively significantly improves the performance gain and the considered RSMA system outperforms the conventional multiple schemes in terms rate and user-fairness. Also, the exploitation of spatial correlation among each RIS elements i.e., non-diagonal phase-matrices at each RIS achieve better performance that conventional diagonal phase-matrices setting.

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Simultaneously Transmitting and Reflecting (STAR) Intelligent Omni-Surfaces, Their Modeling and Implementation

Cited by 6 publications

References 16 publications

STAR-RISs: A Correlated T&R Phase-Shift Model and Practical Phase-Shift Configuration Strategies

STAR-RISs: A Correlated T&R Phase-Shift Model and Practical Phase-Shift Configuration Strategies

Intelligent Omni-Surfaces (IOSs) for the MIMO Broadcast Channel

Rate-Splitting Multiple Access and Dynamic User Clustering for Sum-Rate Maximization in Multiple RISs-Aided Uplink mmWave System

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