Minimization of Power Consumption for NOMA-Assisted UAV Uplink Networks with Imperfect SIC Receiver

Introduction: Unmanned Aerial Vehicle (UAV) communication networks can move in three-dimensional (3D) space, which can lead to a higher Line of Sight (LoS) probability for wireless communication channels between network nodes. Non-Orthogonal Multiple Access (NOMA) techniques are one of the proposed methods to overcome emerging challenges and meet requirements in the fifth (5G) and sixth (6G) generations of cellular systems. Due to the utilisation of an imperfect Successive Interference Cancellation (SIC) receiver, the performance of the NOMA scheme is vulnerable to error propagation. This paper aims to minimise the power consumption of the NOMA-UAV uplink network, which has limited energy resources. In addition, the impact of Channel State Information (CSI) on resource allocation methods is analysed. Methods: The hybrid multiple access schemes are introduced to minimise the sum power in the NOMA-UAV uplink network, subject to minimum data rate and available resource constraints. The frequency sub-bands and transmission power are jointly optimised to decrease the impact of error propagation in the SIC receiver via three hybrid multiple access models, including (i) a hybrid NOMA and OMA scheme with user grouping on multi-NOMA sub-bands, (ii) a hybrid NOMA and OMA scheme with one NOMA sub-band, and (iii) a multi-NOMA sub-bands scheme. The iterative Sequential Quadratic Programming (SQP) algorithm is employed to solve the optimisation problems. Results: The numerical results show the effectiveness of the proposed hybrid schemes in terms of power consumption compared to the conventional NOMA scheme as benchmarks, where the improvement ratio is more than 20%. The hybrid schemes outperform the NOMA schemes reported in other papers, where the performance was compared relative to the OMA scheme. Discussion: The high diversity of available resources in the hybrid multiple access schemes contributed to achieving the best performance in terms of sum power, which negatively affects the time cost performance. Conclusion: Considering an imperfect SIC receiver, available resources in the NOMA-UAV uplink network are optimised at the ground base station to decrease the transmission power of the UAV communication system, which enhances the energy efficiency of UAVs.

Authors

Institutions

Publication Details

Journal
International Journal of Sensors Wireless Communications and Control
Published
2026-01-05
DOI
https://doi.org/10.2174/0122103279397411251014043614
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Minimization of Power Consumption for NOMA-Assisted UAV Uplink Networks with Imperfect SIC Receiver

Osama Mahmoud, Wissam Altabban, Khaldoun Khorzom
International Journal of Sensors Wireless Communications and Control
UAV Applications and Optimization
article

Minimization of Power Consumption for NOMA-Assisted UAV Uplink Networks with Imperfect SIC Receiver

Osama Mahmoud, Wissam Altabban, Khaldoun Khorzom
article en

Abstract

Introduction: Unmanned Aerial Vehicle (UAV) communication networks can move in three-dimensional (3D) space, which can lead to a higher Line of Sight (LoS) probability for wireless communication channels between network nodes. Non-Orthogonal Multiple Access (NOMA) techniques are one of the proposed methods to overcome emerging challenges and meet requirements in the fifth (5G) and sixth (6G) generations of cellular systems. Due to the utilisation of an imperfect Successive Interference Cancellation (SIC) receiver, the performance of the NOMA scheme is vulnerable to error propagation. This paper aims to minimise the power consumption of the NOMA-UAV uplink network, which has limited energy resources. In addition, the impact of Channel State Information (CSI) on resource allocation methods is analysed. Methods: The hybrid multiple access schemes are introduced to minimise the sum power in the NOMA-UAV uplink network, subject to minimum data rate and available resource constraints. The frequency sub-bands and transmission power are jointly optimised to decrease the impact of error propagation in the SIC receiver via three hybrid multiple access models, including (i) a hybrid NOMA and OMA scheme with user grouping on multi-NOMA sub-bands, (ii) a hybrid NOMA and OMA scheme with one NOMA sub-band, and (iii) a multi-NOMA sub-bands scheme. The iterative Sequential Quadratic Programming (SQP) algorithm is employed to solve the optimisation problems. Results: The numerical results show the effectiveness of the proposed hybrid schemes in terms of power consumption compared to the conventional NOMA scheme as benchmarks, where the improvement ratio is more than 20%. The hybrid schemes outperform the NOMA schemes reported in other papers, where the performance was compared relative to the OMA scheme. Discussion: The high diversity of available resources in the hybrid multiple access schemes contributed to achieving the best performance in terms of sum power, which negatively affects the time cost performance. Conclusion: Considering an imperfect SIC receiver, available resources in the NOMA-UAV uplink network are optimised at the ground base station to decrease the transmission power of the UAV communication system, which enhances the energy efficiency of UAVs.

International Journal of Sensors Wireless Communications and ControlVol. 16
Higher Institute for Applied Sciences and Technology (SY)
Affordable and clean energy
Openalex Percentile: Top 71%
UAV Applications and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.