Performance Analysis of IRS-Assisted NOMA Networks With Randomly Deployed Users

Zheng Yang; Peng Xu; Gaojie Chen; Yi Wu; Zhiguo Ding

doi:10.1109/JSYST.2022.3195557

Performance Analysis of IRS-Assisted NOMA Networks With Randomly Deployed Users

Zheng Yang
, Peng Xu
, Gaojie Chen
, Yi Wu
, Zhiguo Ding

Electrical Engineering

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

In this article, we investigate the intelligent reflecting surface (IRS)-assisted downlink nonorthogonal multiple access (NOMA) networks, where the users are randomly deployed in a disk. The randomly deployed users are divided into two groups, named center group and edge group, and then two distance-dependent user selection schemes are proposed. The developed closed-form expressions of outage probability and average rate for the proposed two user selection schemes in IRS-assisted NOMA networks are derived, as well as the asymptotic results at high signal-to-noise ratio (SNR) and the number of the reflecting number of the IRS trends to infinity, respectively. The asymptotic analysis results of outage probability for cell-edge user decay as <inline-formula><tex-math notation="LaTeX">$\frac{\ln \mathrm{SNR}}{\mathrm{SNR} ^{K+1}}$</tex-math></inline-formula>, and the achieved diversity gain is <inline-formula><tex-math notation="LaTeX">$K+1$</tex-math></inline-formula>, at high SNR region, where <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula> denotes the number of elements of the IRS. Furthermore, as <inline-formula><tex-math notation="LaTeX">$K \rightarrow \infty$</tex-math></inline-formula>, the asymptotic average rate of cell-edge user only depends on the power allocation factor of cell-center user. In addition, compared to IRS-assisted orthogonal multiple access networks, the IRS-assisted NOMA networks can always realize lower outage performance and higher average rate. Finally, Monte–Carlo simulation results are provided to verify the accuracy of the developed analytical results for the proposed two user selection schemes.

Original language	British English
Pages (from-to)	1-12
Number of pages	12
Journal	IEEE Systems Journal
DOIs	https://doi.org/10.1109/JSYST.2022.3195557
State	Accepted/In press - 2022

Keywords

Array signal processing
Average rate
Base stations
Downlink
Integrated circuits
intelligent reflecting surfaces (IRS)
NOMA
nonorthogonal multiple access (NOMA)
outage probability
Resource management
Signal to noise ratio

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10.1109/JSYST.2022.3195557

Cite this

@article{eaee8694e0c049628a9af1d39729cfc4,

title = "Performance Analysis of IRS-Assisted NOMA Networks With Randomly Deployed Users",

abstract = "In this article, we investigate the intelligent reflecting surface (IRS)-assisted downlink nonorthogonal multiple access (NOMA) networks, where the users are randomly deployed in a disk. The randomly deployed users are divided into two groups, named center group and edge group, and then two distance-dependent user selection schemes are proposed. The developed closed-form expressions of outage probability and average rate for the proposed two user selection schemes in IRS-assisted NOMA networks are derived, as well as the asymptotic results at high signal-to-noise ratio (SNR) and the number of the reflecting number of the IRS trends to infinity, respectively. The asymptotic analysis results of outage probability for cell-edge user decay as \$\textbackslash{}frac\{\textbackslash{}ln \textbackslash{}mathrm\{SNR\}\}\{\textbackslash{}mathrm\{SNR\} \textasciicircum{}\{K+1\}\}\$, and the achieved diversity gain is \$K+1\$, at high SNR region, where \$K\$ denotes the number of elements of the IRS. Furthermore, as \$K \textbackslash{}rightarrow \textbackslash{}infty\$, the asymptotic average rate of cell-edge user only depends on the power allocation factor of cell-center user. In addition, compared to IRS-assisted orthogonal multiple access networks, the IRS-assisted NOMA networks can always realize lower outage performance and higher average rate. Finally, Monte–Carlo simulation results are provided to verify the accuracy of the developed analytical results for the proposed two user selection schemes.",

keywords = "Array signal processing, Average rate, Base stations, Downlink, Integrated circuits, intelligent reflecting surfaces (IRS), NOMA, nonorthogonal multiple access (NOMA), outage probability, Resource management, Signal to noise ratio",

author = "Zheng Yang and Peng Xu and Gaojie Chen and Yi Wu and Zhiguo Ding",

note = "Publisher Copyright: IEEE",

year = "2022",

doi = "10.1109/JSYST.2022.3195557",

language = "British English",

pages = "1--12",

journal = "IEEE Systems Journal",

issn = "1932-8184",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Performance Analysis of IRS-Assisted NOMA Networks With Randomly Deployed Users

AU - Yang, Zheng

AU - Xu, Peng

AU - Chen, Gaojie

AU - Wu, Yi

AU - Ding, Zhiguo

N1 - Publisher Copyright: IEEE

PY - 2022

Y1 - 2022

N2 - In this article, we investigate the intelligent reflecting surface (IRS)-assisted downlink nonorthogonal multiple access (NOMA) networks, where the users are randomly deployed in a disk. The randomly deployed users are divided into two groups, named center group and edge group, and then two distance-dependent user selection schemes are proposed. The developed closed-form expressions of outage probability and average rate for the proposed two user selection schemes in IRS-assisted NOMA networks are derived, as well as the asymptotic results at high signal-to-noise ratio (SNR) and the number of the reflecting number of the IRS trends to infinity, respectively. The asymptotic analysis results of outage probability for cell-edge user decay as $\frac{\ln \mathrm{SNR}}{\mathrm{SNR} ^{K+1}}$, and the achieved diversity gain is $K+1$, at high SNR region, where $K$ denotes the number of elements of the IRS. Furthermore, as $K \rightarrow \infty$, the asymptotic average rate of cell-edge user only depends on the power allocation factor of cell-center user. In addition, compared to IRS-assisted orthogonal multiple access networks, the IRS-assisted NOMA networks can always realize lower outage performance and higher average rate. Finally, Monte–Carlo simulation results are provided to verify the accuracy of the developed analytical results for the proposed two user selection schemes.

AB - In this article, we investigate the intelligent reflecting surface (IRS)-assisted downlink nonorthogonal multiple access (NOMA) networks, where the users are randomly deployed in a disk. The randomly deployed users are divided into two groups, named center group and edge group, and then two distance-dependent user selection schemes are proposed. The developed closed-form expressions of outage probability and average rate for the proposed two user selection schemes in IRS-assisted NOMA networks are derived, as well as the asymptotic results at high signal-to-noise ratio (SNR) and the number of the reflecting number of the IRS trends to infinity, respectively. The asymptotic analysis results of outage probability for cell-edge user decay as $\frac{\ln \mathrm{SNR}}{\mathrm{SNR} ^{K+1}}$, and the achieved diversity gain is $K+1$, at high SNR region, where $K$ denotes the number of elements of the IRS. Furthermore, as $K \rightarrow \infty$, the asymptotic average rate of cell-edge user only depends on the power allocation factor of cell-center user. In addition, compared to IRS-assisted orthogonal multiple access networks, the IRS-assisted NOMA networks can always realize lower outage performance and higher average rate. Finally, Monte–Carlo simulation results are provided to verify the accuracy of the developed analytical results for the proposed two user selection schemes.

KW - Array signal processing

KW - Average rate

KW - Base stations

KW - Downlink

KW - Integrated circuits

KW - intelligent reflecting surfaces (IRS)

KW - NOMA

KW - nonorthogonal multiple access (NOMA)

KW - outage probability

KW - Resource management

KW - Signal to noise ratio

UR - https://www.scopus.com/pages/publications/85136884713

U2 - 10.1109/JSYST.2022.3195557

DO - 10.1109/JSYST.2022.3195557

M3 - Article

AN - SCOPUS:85136884713

SN - 1932-8184

SP - 1

EP - 12

JO - IEEE Systems Journal

JF - IEEE Systems Journal

ER -

Performance Analysis of IRS-Assisted NOMA Networks With Randomly Deployed Users

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