Optimal partitioning of reconfigurable intelligent surfaces for uplink NOMA networks
Optimal partitioning of reconfigurable intelligent surfaces for uplink NOMA networks
In this work, we examine the potential of reconfigurable intelligent surfaces (RISs) to facilitate and enhance uplink (UL) transmissions in grant-free non-orthogonal multiple access (GF-NOMA) networks. The proposed RIS-assisted GF-NOMA approach employs virtual partitioning of RIS, with each partition tailored to optimize channel conditions for individual NOMA user equipment (UE). The resulting channel gain disparity bolsters the NOMA gain and obviates the necessity for UL power control of the grant-based NOMA schemes. Our approach is evaluated under three practical operational regimes: 1) quality-of-service (QoS) sufficient regime, 2) efficient RIS usage regime, and 3) max-min fair regime, all subject to UL-QoS constraints. We derive closed-form solutions to elucidate how optimal RIS partitioning can fulfill UL-QoS requirements across all three operational regimes. Comprehensive simulations are conducted to validate the precision of our analytical findings, demonstrating that the proposed approach substantially improves wireless communication system performance while mitigating signaling overhead and computational complexity.
Grant-free non-orthogonal multiple access (NOMA), optimization, passive beamforming, reconfigurable intelligent surface (RIS), uplink transmission
Makin, Madi
bf8c6a8f-ab2e-4d5f-8435-5899351be242
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Arzykulov, Sultangali
25fb1b83-665d-4fe7-9e56-81cacc2f8e7a
Eltawil, Ahmed M.
5eb9e965-5ec8-4da1-baee-c3cab0fb2a72
Nauryzbayev, Galymzhan
3fbbb5ed-dc25-4c5a-943c-7fd329867c75
1 January 2024
Makin, Madi
bf8c6a8f-ab2e-4d5f-8435-5899351be242
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Arzykulov, Sultangali
25fb1b83-665d-4fe7-9e56-81cacc2f8e7a
Eltawil, Ahmed M.
5eb9e965-5ec8-4da1-baee-c3cab0fb2a72
Nauryzbayev, Galymzhan
3fbbb5ed-dc25-4c5a-943c-7fd329867c75
Makin, Madi, Celik, Abdulkadir, Arzykulov, Sultangali, Eltawil, Ahmed M. and Nauryzbayev, Galymzhan
(2024)
Optimal partitioning of reconfigurable intelligent surfaces for uplink NOMA networks.
In 2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024.
IEEE.
6 pp
.
(doi:10.1109/PIMRC59610.2024.10817291).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this work, we examine the potential of reconfigurable intelligent surfaces (RISs) to facilitate and enhance uplink (UL) transmissions in grant-free non-orthogonal multiple access (GF-NOMA) networks. The proposed RIS-assisted GF-NOMA approach employs virtual partitioning of RIS, with each partition tailored to optimize channel conditions for individual NOMA user equipment (UE). The resulting channel gain disparity bolsters the NOMA gain and obviates the necessity for UL power control of the grant-based NOMA schemes. Our approach is evaluated under three practical operational regimes: 1) quality-of-service (QoS) sufficient regime, 2) efficient RIS usage regime, and 3) max-min fair regime, all subject to UL-QoS constraints. We derive closed-form solutions to elucidate how optimal RIS partitioning can fulfill UL-QoS requirements across all three operational regimes. Comprehensive simulations are conducted to validate the precision of our analytical findings, demonstrating that the proposed approach substantially improves wireless communication system performance while mitigating signaling overhead and computational complexity.
This record has no associated files available for download.
More information
Published date: 1 January 2024
Venue - Dates:
35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024, , Valencia, Spain, 2024-09-02 - 2024-09-05
Keywords:
Grant-free non-orthogonal multiple access (NOMA), optimization, passive beamforming, reconfigurable intelligent surface (RIS), uplink transmission
Identifiers
Local EPrints ID: 505794
URI: http://eprints.soton.ac.uk/id/eprint/505794
ISSN: 2166-9570
PURE UUID: 65653d60-26be-4822-93c8-d7d1e5d07348
Catalogue record
Date deposited: 20 Oct 2025 16:33
Last modified: 21 Oct 2025 02:15
Export record
Altmetrics
Contributors
Author:
Madi Makin
Author:
Abdulkadir Celik
Author:
Sultangali Arzykulov
Author:
Ahmed M. Eltawil
Author:
Galymzhan Nauryzbayev
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics