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  5. IRS-Aided Wireless Relaying: Optimal Deployment and Capacity Scaling.

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Preprint
English
2021

IRS-Aided Wireless Relaying: Optimal Deployment and Capacity Scaling.

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English
2021
arXiv (Cornell University)

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Rui Zhang
Rui Zhang

The Chinese University of Hong Kong

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Zhenyu Kang
Changsheng You
Rui Zhang

Abstract

In this letter, we consider an intelligent reflecting surface (IRS)-aided wireless relaying system, where a decode-and-forward relay (R) is employed to forward data from a source (S) to a destination (D), aided by M passive reflecting elements. We consider two practical IRS deployment strategies, namely, single-IRS deployment where all reflecting elements are mounted on one single IRS that is deployed near S, R, or D, and multi-IRS deployment where the reflecting elements are allocated over three separate IRSs which are deployed near S, R, and D, respectively. Under the line-of-sight (LoS) channel model, we characterize the capacity scaling orders with respect to an increasing M for the IRS-aided relay system with different IRS deployment strategies. For single-IRS deployment, we show that deploying the IRS near R achieves the highest capacity as compared to that near S or D. While for multi-IRS deployment, we propose a practical cooperative IRS passive beamforming design which is analytically shown to achieve a larger capacity scaling order than the optimal single-IRS deployment (i.e., near R) when M is sufficiently large. Numerical examples are provided, which validate our theoretical results.

How to cite this publication

Zhenyu Kang, Changsheng You, Rui Zhang (2021). IRS-Aided Wireless Relaying: Optimal Deployment and Capacity Scaling.. arXiv (Cornell University)

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Publication Details

Type

Preprint

Year

2021

Authors

3

Datasets

0

Total Files

0

Language

English

Journal

arXiv (Cornell University)

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