Exploiting User Clustering and Fixed Power Allocation for Multi-Antenna UAV-Assisted IoT Systems Article Swipe
Sang Quang Nguyen
,
Anh‐Tu Le
,
Chi‐Bao Le
,
Phu Tran Tin
,
Yong–Hwa Kim
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/s23125537
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/s23125537
Internet of Things (IoT) systems cooperative with unmanned aerial vehicles (UAVs) have been put into use for more than ten years, from transportation to military surveillance, and they have been shown to be worthy of inclusion in the next wireless protocols. Therefore, this paper studies user clustering and the fixed power allocation approach by placing multi-antenna UAV-mounted relays for extended coverage areas and achieving improved performance for IoT devices. In particular, the system enables UAV-mounted relays with multiple antennas together with non-orthogonal multiple access (NOMA) to provide a potential way to enhance transmission reliability. We presented two cases of multi-antenna UAVs such as maximum ratio transmission and the best selection to highlight the benefits of the antenna-selections approach with low-cost design. In addition, the base station managed its IoT devices in practical scenarios with and without direct links. For two cases, we derive closed-form expressions of outage probability (OP) and closed-form approximation ergodic capacity (EC) generated for both devices in the main scenario. The outage and ergodic capacity performances in some scenarios are compared to confirm the benefits of the considered system. The number of antennas was found to have a crucial impact on the performances. The simulation results show that the OP for both users strongly decreases when the signal-to-noise ratio (SNR), number of antennas, and fading severity factor of Nakagami-m fading increase. The proposed scheme outperforms the orthogonal multiple access (OMA) scheme in outage performance for two users. The analytical results match Monte Carlo simulations to confirm the exactness of the derived expressions.
Related Topics
Concepts
Nakagami distribution
Computer science
Transmission (telecommunications)
Fading
Base station
Cluster analysis
Ergodic theory
Antenna (radio)
Reliability (semiconductor)
Computer network
Electronic engineering
Power (physics)
Real-time computing
Channel (broadcasting)
Telecommunications
Engineering
Mathematics
Quantum mechanics
Mathematical analysis
Machine learning
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s23125537
- https://www.mdpi.com/1424-8220/23/12/5537/pdf?version=1686647958
- OA Status
- gold
- Cited By
- 8
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380682445
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4380682445Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s23125537Digital Object Identifier
- Title
-
Exploiting User Clustering and Fixed Power Allocation for Multi-Antenna UAV-Assisted IoT SystemsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-13Full publication date if available
- Authors
-
Sang Quang Nguyen, Anh‐Tu Le, Chi‐Bao Le, Phu Tran Tin, Yong–Hwa KimList of authors in order
- Landing page
-
https://doi.org/10.3390/s23125537Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/23/12/5537/pdf?version=1686647958Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/1424-8220/23/12/5537/pdf?version=1686647958Direct OA link when available
- Concepts
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Nakagami distribution, Computer science, Transmission (telecommunications), Fading, Base station, Cluster analysis, Ergodic theory, Antenna (radio), Reliability (semiconductor), Computer network, Electronic engineering, Power (physics), Real-time computing, Channel (broadcasting), Telecommunications, Engineering, Mathematics, Quantum mechanics, Mathematical analysis, Machine learning, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 3, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
50Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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