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Energy-efficient framework based on optimal antenna selection in S-NOMA supported UAV IoT networks
Lav Soni1, Ashu Taneja1, Nayef Alqahtani2
1Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Plos One
|January 2, 2026
Summary
This study introduces an energy-efficient framework for Unmanned Aerial Vehicle (UAV) assisted Internet-of-Things (IoT) networks using spatial Non-Orthogonal Multiple Access (S-NOMA). The proposed system significantly enhances data rates and energy efficiency for sustainable IoT connectivity.
Area of Science:
- Wireless Communication Networks
- Internet of Things (IoT)
- Sustainable Energy Systems
Background:
- The expanding Internet-of-Things (IoT) necessitates energy-efficient solutions due to high emissions and energy consumption.
- Unmanned Aerial Vehicle (UAV) assisted networks offer a promising approach to enhance IoT connectivity.
- Achieving energy sustainability in heterogeneous terrestrial and non-terrestrial IoT networks is a critical challenge.
Purpose of the Study:
- To present an energy-efficient framework for UAV-assisted IoT networks utilizing spatial Non-Orthogonal Multiple Access (S-NOMA).
- To develop an antenna selection algorithm for user fairness and optimize power consumption models.
- To analyze and improve the energy efficiency and data rate performance of S-NOMA in UAV-IoT systems.
Main Methods:
- Development of a spatial Non-Orthogonal Multiple Access (S-NOMA) framework for UAV-assisted IoT.
- Proposal of an antenna selection algorithm to ensure user fairness.
- Formulation of air-to-ground communication links and a power consumption model (including transmit, circuit, and UAV hovering power).
Main Results:
- The proposed S-NOMA framework with optimal antenna selection demonstrated superior data rate and energy efficiency compared to conventional NOMA and random schemes.
- At 30 dB SNR, the proposed method achieved a data rate of 15.2 bps/Hz, significantly outperforming conventional NOMA (6.4 bps/Hz).
- Energy efficiency improved by 14.4% at 25 dBm transmit power with the proposed antenna selection over random selection, attributed to enhanced spatial gain and power-aware selection.
Conclusions:
- The proposed S-NOMA framework with optimal antenna selection offers a sustainable solution for UAV-assisted IoT networks.
- Enhanced spatial gain and power-aware antenna selection are key factors in improving energy efficiency and data rates.
- The framework effectively addresses the challenge of energy sustainability in expanding heterogeneous IoT networks.
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