Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access

Yang, Gang; Xu, Xinyue; Liang, Ying-Chang

doi:10.1109/wcnc45663.2020.9120476

Cited by 206 publications

(178 citation statements)

References 18 publications

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“…In [213], the authors maximize the minimum rate among the users of an RIS-assisted downlink NOMA system. The optimization problem is formulated in terms of the transmit beamforming vector and the RIS phase shifts.…”

Section: Non-orthogonal Multiple Accessmentioning

confidence: 99%

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Renzo

Zappone

Debbah

et al. 2020

IEEE J. Select. Areas Commun.

2,226

918

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What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

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Section: Non-orthogonal Multiple Accessmentioning

confidence: 99%

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Renzo

Zappone

Debbah

et al. 2020

IEEE J. Select. Areas Commun.

2,226

918

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“…The suboptimal transmit beamforming of the active antenna array at the AP and the reflect beamforming of passive phase shifters have been achieved by using the AOM. Moreover, due to the advantage of IRS in capacity improvement, it has also been adopted to enhance the performance of various communication systems, such as Terahertz communication system [18], simultaneous wireless information and power transfer (SWIPT) system [19], [20], and non-orthogonal multiple access (NOMA) system [21]- [23]. The summary of existing work and comparison of the problem formulation along with solution domains is provided in Table I.…”

Section: A Related Workmentioning

confidence: 99%

“…Define g sm and g ss as the channel gain from the SBS to the MCU and the SBS to the SCU. [17] single-tier multiuser IRS-based MISO system min: total transmit power inter-cell interference beamforming and RC suboptimal, closed-form [15] single-tier single-user IRS-based MISO system max: data rate inter-cell interference beamforming and RC suboptimal, no close-form [16] single-tier multiuser IRS-based MISO system max: EE inter-cell interference power allocation and RC suboptimal, no close-form [18] single-tier multiuser IRS-based MISO system max: sum rate inter-cell interference beamforming and RC suboptimal, no close-form [19] single-tier multiuser MISO IRS-SWIPT system min: total transmit power Inter-cell interference beamforming and RC suboptimal, close-form [20] single-tier multiuser MIMO IRS-SWIPT system max: weighted sum rate inter-cell interference beamforming and RC suboptimal, close-form [21] single-tier multiuser SISO IRS-NOMA system max-min: SINR inter-cell interference power allocation and RC suboptimal, no close-form [22] single-tier multiuser MISO IRS-NOMA system max: sum rate inter-cell interference beamforming and RC suboptimal, no close-form [23] single-tier multiuser MISO IRS-NOMA system min: total transmit power inter-cell interference beamforming and RC suboptimal, no close-form in this paper two-tier multiuser IRS-based HetNets max: sum rate inter-cell interference, cross-tier interference power allocation and RC optimal and suboptimal, closed-form coefficient matrix of the IRS. Since we aim to obtain the maximum designed signal, therefore, the amplitude coefficient is set as β m = 1 for simplicity [17].…”

Section: A System Modelmentioning

confidence: 99%

“…Generally, the solution X of P5 may not satisfy its rank constraint, namely, rank(X) = 1, therefore the optimal objective value of P5 only serves an upper bound of P4. To solve this problem and obtain a rank-one solution, the Gaussian randomization scheme and the singular-valuedecomposition scheme are used [17], [21], [35]. The iterative RA algorithm is summarized in Algorithm 1.…”

Section: P3mentioning

confidence: 99%

See 1 more Smart Citation

Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

Xu¹,

Qin²,

Zhao³

et al. 2020

Preprint

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Intelligent reflecting surface (IRS)-enabled communication systems provide higher system capacity and spectral efficiency by reflecting the incident signals from transmitters in a low-cost passive reflecting way. However, it poses new challenges in resource allocation due to surrounding interference and phase shift, especially when IRS is employed in heterogeneous networks (HetNets). In this paper, a joint power allocation and phase shift optimization problem is studied for the downlink IRS-enabled HetNet, in which the IRS is deployed to enhance the communications between small cell users (SCUs) and associated base station (BS). The signal-to-interference-plus-noise ratio (SINR) received at the SCU is maximized by jointly optimizing the transmit power of the small-cell BS and the phase shift of the IRS, subject to the constraints on the minimum SINR requirement of the macro-cell user (MCU) and the phase shift. Although the formulated problem is non-convex, we develop an optimal power allocation and the IRS's passive array coefficient solution for the single-user scenario. For the multi-user scenario, we propose an iterative algorithm to maximize the total rates of SCUs for obtaining a suboptimal solution by an alternating iteration manner, where the sum of multiple-ratio fractional programming problem is converted into a convex semidefinite program (SDP) problem. Simulation results show that the proposed algorithm significantly improves the achieved transmission rates of SCUs compared to the case without the IRS.

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“…An IRS is an ultra-thin planar structure composed of a large number of reflecting elements with a size smaller than the signal wavelength, known as meta-atoms [5], [6]. The key advantage of IRS structures is that each meta-atom can be dynamically tuned by software with distinct phases and amplitudes of reflection so that they can collaboratively forward the impinging waves with, ideally, any desired radiation pattern, like a hologram.…”

Section: Introductionmentioning

confidence: 99%

What Role Do Intelligent Reflecting Surfaces Play in Non-Orthogonal Multiple Access?

Sena¹,

Nardelli²

2020

Preprint

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Massive multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) are two key techniques for enabling massive connectivity in future wireless networks. A massive MIMO-NOMA system can deliver remarkable spectral improvements and reduced communication latency. Nevertheless, the uncontrollable stochastic behavior of the wireless channels can still degrade its performance. In this context, intelligent reflecting surface (IRS) has arisen as a promising technology for smartly overcoming the harmful effects of the wireless environment. The disruptive IRS concept of controlling the propagation channels via software can provide attractive performance gains to the communication networks, including higher data rates, improved user fairness, and, possibly, higher energy efficiency. In this article, in contrast to the existing literature, we demonstrate the main roles of IRSs in MIMO-NOMA systems. Specifically, we identify and perform a comprehensive discussion of the main performance gains that can be achieved in IRS-assisted massive MIMO-NOMA (IRS-NOMA) networks. We outline exciting futuristic use case scenarios for IRS-NOMA and expose the main related challenges and future research directions. Furthermore, throughout the article, we support our in-depth discussions with representative numerical results.

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Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access

Cited by 206 publications

References 18 publications

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

What Role Do Intelligent Reflecting Surfaces Play in Non-Orthogonal Multiple Access?

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