Rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors

Widad Belaoura; Zineb Yamoutene; Muhammad Zeeshan Shakir

doi:10.1109/ICEEAC61226.2024.10576391

Rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors

Widad Belaoura
, Zineb Yamoutene
, Muhammad Zeeshan Shakir

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

24 Downloads (Pure)

Abstract

The Intelligent Reflecting Surface (IRS) represents a revolutionary technology for effectively enhancing the performance of Internet-of-Things (IoT) networks owing to its ability of customizing the wireless propagation environment and compatibility with advanced communication techniques, such as non-orthogonal multiple-access (NOMA). This paper investigates the impact of imperfect channel state information (CSI) on the achievable data rate of IRS-Aided downlink NOMA-enabled IoT framework over Rician fading channels. Specifically, the imperfect CSI is considered from the IRS to the IoT devices. The results demonstrated that imperfect CSI has a significant impact on the achievable rate performance of the far and near IoT devices, which are also different under different numbers of reflecting units.

Original language	English
Title of host publication	2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC
Publisher	IEEE
DOIs	https://doi.org/10.1109/ICEEAC61226.2024.10576391
Publication status	Published - 8 Jul 2024

Keywords

intelligent reflecting surface (IRS)
6G
NOMA
imperfect CSI
internet-of-things (IoT)
achievable rate

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10.1109/ICEEAC61226.2024.10576391

2023 03 01 Belaoura et al NOMA accepted - for PureAccepted author manuscript, 422 KBLicence: CC BY 4.0

Cite this

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title = "Rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors",

abstract = "The Intelligent Reflecting Surface (IRS) represents a revolutionary technology for effectively enhancing the performance of Internet-of-Things (IoT) networks owing to its ability of customizing the wireless propagation environment and compatibility with advanced communication techniques, such as non-orthogonal multiple-access (NOMA). This paper investigates the impact of imperfect channel state information (CSI) on the achievable data rate of IRS-Aided downlink NOMA-enabled IoT framework over Rician fading channels. Specifically, the imperfect CSI is considered from the IRS to the IoT devices. The results demonstrated that imperfect CSI has a significant impact on the achievable rate performance of the far and near IoT devices, which are also different under different numbers of reflecting units.",

keywords = "intelligent reflecting surface (IRS), 6G, NOMA, imperfect CSI, internet-of-things (IoT), achievable rate",

author = "Widad Belaoura and Zineb Yamoutene and Shakir, \{Muhammad Zeeshan\}",

year = "2024",

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day = "8",

doi = "10.1109/ICEEAC61226.2024.10576391",

language = "English",

booktitle = "2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC",

publisher = "IEEE",

address = "United States",

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TY - GEN

T1 - Rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors

AU - Belaoura, Widad

AU - Yamoutene, Zineb

AU - Shakir, Muhammad Zeeshan

PY - 2024/7/8

Y1 - 2024/7/8

N2 - The Intelligent Reflecting Surface (IRS) represents a revolutionary technology for effectively enhancing the performance of Internet-of-Things (IoT) networks owing to its ability of customizing the wireless propagation environment and compatibility with advanced communication techniques, such as non-orthogonal multiple-access (NOMA). This paper investigates the impact of imperfect channel state information (CSI) on the achievable data rate of IRS-Aided downlink NOMA-enabled IoT framework over Rician fading channels. Specifically, the imperfect CSI is considered from the IRS to the IoT devices. The results demonstrated that imperfect CSI has a significant impact on the achievable rate performance of the far and near IoT devices, which are also different under different numbers of reflecting units.

AB - The Intelligent Reflecting Surface (IRS) represents a revolutionary technology for effectively enhancing the performance of Internet-of-Things (IoT) networks owing to its ability of customizing the wireless propagation environment and compatibility with advanced communication techniques, such as non-orthogonal multiple-access (NOMA). This paper investigates the impact of imperfect channel state information (CSI) on the achievable data rate of IRS-Aided downlink NOMA-enabled IoT framework over Rician fading channels. Specifically, the imperfect CSI is considered from the IRS to the IoT devices. The results demonstrated that imperfect CSI has a significant impact on the achievable rate performance of the far and near IoT devices, which are also different under different numbers of reflecting units.

KW - intelligent reflecting surface (IRS)

KW - 6G

KW - NOMA

KW - imperfect CSI

KW - internet-of-things (IoT)

KW - achievable rate

U2 - 10.1109/ICEEAC61226.2024.10576391

DO - 10.1109/ICEEAC61226.2024.10576391

M3 - Conference contribution

BT - 2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC

PB - IEEE

ER -

Rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors

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Keywords

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