Outage Probability Analysis and Minimization in Intelligent Reflecting Surface-Assisted MISO Systems

Guo, Chang; Cui, Ying; Yang, Feng; Ding, Lianghui

doi:10.1109/lcomm.2020.2975182

Cited by 76 publications

(52 citation statements)

References 5 publications

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“…In [121], the authors study an RIS-assisted MISO system in which a base station equipped with multiple antennas arranged in a uniform rectangular array serves a single-antenna user with the help of an RIS equipped with multiple elements arranged in a uniform rectangular array. The authors consider a Rician fading model, where the non-line-of-sight components vary slowly and the line-of-sight components do not change.…”

Section: H Performance Evaluationmentioning

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.

2,006

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: H Performance Evaluationmentioning

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.

2,006

918

View full text Add to dashboard Cite

show abstract

“…Subsequently, we obtain those parameters as shown in the theorem. We now define = + =1 , which has mean and second moment are computed as Let us match random variable to a Gamma distribution whose the shape and scale parameters are defined as in (9). By introducing a new random variable = 2 , then the CDF of can be directly drawn from as ( ) = √ and we close the proof here.…”

Section: Numerical Resultsmentioning

confidence: 95%

“…physical layer security [2] together with references therein. While those previous works are utterly based on small-scale fading, only a few related works pay attention to system analyses utilizing large-scale fading coefficients, but under the asymptotic regime, such as [8] for a large IRS or [9] for multiple IRSs. In [10], the authors computed the closed-form expression of the coverage property for a large number of the optimal phase shifts and no direct link between the source and destination.…”

Section: Introductionmentioning

confidence: 99%

Coverage Probability and Ergodic Capacity of Intelligent Reflecting Surface-Enhanced Communication Systems

Chien

Chatzinotas

et al. 2021

IEEE Commun. Lett.

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This paper studies the performance of a singleinput single-output (SISO) system enhanced by the assistance of an intelligent reflecting surface (IRS), which is equipped with a finite number of elements under Rayleigh fading channels. From the instantaneous channel capacity, we compute a closedform expression of the coverage probability as a function of statistical channel information only. A scaling law of the coverage probability and the number of phase shifts is further obtained. The ergodic capacity is derived, then a simple upper bound to simplify matters of utilizing the symbolic functions and can be applied for a long period of time. Numerical results manifest the tightness and effectiveness of our closed-form expressions compared with Monte-Carlo simulations.

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“…e AIRS consists of N � N x × N y elements, with half-wavelength spacing of the antennas/elements. Similar to [13,22,[29][30][31][32][33], we characterize the channel from the l-th AP to the AIRS G l ∈ C N×M as follows:…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Power Optimization for Aerial Intelligent Reflecting Surface-Aided Cell-Free Massive MIMO-Based Wireless Sensor Network

Zhou

Chunguo

et al. 2021

Security and Communication Networks

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Intelligent reflecting surfaces (IRSs) have significant advantages in enhancing the coverage and reducing the deployment cost of wireless networks. This paper studies an aerial IRS- (AIRS-) enhanced cell-free massive multiple-input multiple-output- (MIMO-) based wireless sensor network (WSN) in which multiple access points (APs) serve several sensor users (SUs). Direct links between the APs and SUs are blocked due to occlusion by tall buildings. Hence, we deploy an AIRS to improve the communication quality of the SUs. Our goal is to minimize the total transmit power of all APs under a given minimum signal-to-interference-plus-noise ratio (SINR) requirement. We propose a joint iterative optimization algorithm by designing an active beamforming mechanism at each AP and a passive beamforming mechanism at the AIRS to solve this problem. Simulation results illustrate the good performance of the proposed method.

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Outage Probability Analysis and Minimization in Intelligent Reflecting Surface-Assisted MISO Systems

Cited by 76 publications

References 5 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

Coverage Probability and Ergodic Capacity of Intelligent Reflecting Surface-Enhanced Communication Systems

Power Optimization for Aerial Intelligent Reflecting Surface-Aided Cell-Free Massive MIMO-Based Wireless Sensor Network

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