Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks

Madi Makin; Sultangali Arzykulov; Khaled M. Rabie; Galymzhan Nauryzbayev

doi:10.1109/csndsp54353.2022.9907962

Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks

Madi Makin, Sultangali Arzykulov, Khaled M. Rabie, Galymzhan Nauryzbayev

Computer, Electrical and Mathematical Sciences and Engineering

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

1 Scopus citations

Abstract

Low latency, high-data rates, and massive connectivity are the requirements for the emerging wireless technologies that will give a chance to high-demanding and progressive innovations in many spheres. Reconfigurable intelligent surfaces (RISs) are considered to be a promising technology for the rising wireless communication standards. This paper studies the large intelligent surface (LIS) enabled wireless network deploying non-orthogonal multiple access (NOMA) over Nakagami-m channels with non-fixed LIS positions. We propose the LIS partitioning method, where various LIS elements serve different NOMA users depending on their quality of service. Moreover, we also examine the effect of imperfect successive interference cancellation, the number of LIS elements, and their allocation amongst the users. The simulations and followed-up discussions are provided regarding the system’s ergodic capacity measurements.

Original language	English (US)
Title of host publication	2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)
Publisher	IEEE
DOIs	https://doi.org/10.1109/csndsp54353.2022.9907962
State	Published - Oct 6 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-11
Acknowledgements: This work was supported by the Nazarbayev University Faculty Development Competitive Research Grants Program under Grant no. 240919FD3935 (PI: G. Nauryzbayev).

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10.1109/csndsp54353.2022.9907962

Cite this

@inproceedings{bda84a32998c46d9a0a126fd8ccc097e,

title = "Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks",

abstract = "Low latency, high-data rates, and massive connectivity are the requirements for the emerging wireless technologies that will give a chance to high-demanding and progressive innovations in many spheres. Reconfigurable intelligent surfaces (RISs) are considered to be a promising technology for the rising wireless communication standards. This paper studies the large intelligent surface (LIS) enabled wireless network deploying non-orthogonal multiple access (NOMA) over Nakagami-m channels with non-fixed LIS positions. We propose the LIS partitioning method, where various LIS elements serve different NOMA users depending on their quality of service. Moreover, we also examine the effect of imperfect successive interference cancellation, the number of LIS elements, and their allocation amongst the users. The simulations and followed-up discussions are provided regarding the system{\textquoteright}s ergodic capacity measurements.",

author = "Madi Makin and Sultangali Arzykulov and Rabie, {Khaled M.} and Galymzhan Nauryzbayev",

note = "KAUST Repository Item: Exported on 2022-10-11 Acknowledgements: This work was supported by the Nazarbayev University Faculty Development Competitive Research Grants Program under Grant no. 240919FD3935 (PI: G. Nauryzbayev).",

year = "2022",

month = oct,

day = "6",

doi = "10.1109/csndsp54353.2022.9907962",

language = "English (US)",

booktitle = "2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)",

publisher = "IEEE",

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T1 - Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks

AU - Makin, Madi

AU - Arzykulov, Sultangali

AU - Rabie, Khaled M.

AU - Nauryzbayev, Galymzhan

N1 - KAUST Repository Item: Exported on 2022-10-11 Acknowledgements: This work was supported by the Nazarbayev University Faculty Development Competitive Research Grants Program under Grant no. 240919FD3935 (PI: G. Nauryzbayev).

PY - 2022/10/6

Y1 - 2022/10/6

N2 - Low latency, high-data rates, and massive connectivity are the requirements for the emerging wireless technologies that will give a chance to high-demanding and progressive innovations in many spheres. Reconfigurable intelligent surfaces (RISs) are considered to be a promising technology for the rising wireless communication standards. This paper studies the large intelligent surface (LIS) enabled wireless network deploying non-orthogonal multiple access (NOMA) over Nakagami-m channels with non-fixed LIS positions. We propose the LIS partitioning method, where various LIS elements serve different NOMA users depending on their quality of service. Moreover, we also examine the effect of imperfect successive interference cancellation, the number of LIS elements, and their allocation amongst the users. The simulations and followed-up discussions are provided regarding the system’s ergodic capacity measurements.

AB - Low latency, high-data rates, and massive connectivity are the requirements for the emerging wireless technologies that will give a chance to high-demanding and progressive innovations in many spheres. Reconfigurable intelligent surfaces (RISs) are considered to be a promising technology for the rising wireless communication standards. This paper studies the large intelligent surface (LIS) enabled wireless network deploying non-orthogonal multiple access (NOMA) over Nakagami-m channels with non-fixed LIS positions. We propose the LIS partitioning method, where various LIS elements serve different NOMA users depending on their quality of service. Moreover, we also examine the effect of imperfect successive interference cancellation, the number of LIS elements, and their allocation amongst the users. The simulations and followed-up discussions are provided regarding the system’s ergodic capacity measurements.

UR - http://hdl.handle.net/10754/682323

UR - https://ieeexplore.ieee.org/document/9907962/

U2 - 10.1109/csndsp54353.2022.9907962

DO - 10.1109/csndsp54353.2022.9907962

M3 - Conference contribution

BT - 2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)

PB - IEEE

ER -

Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks

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