Treffer: Energy-efficient framework based on optimal antenna selection in S-NOMA supported UAV IoT networks.

Owing to the high emissions and increased energy consumption of the expanding heterogeneous internet-of-things (IoT) devices across terrestial and non-terrestial networks, achieving the energy sustainability in future IoT networks is the main challenge. This paper presents an energy efficient framework utilising spatial non orthogonal multiple access (S-NOMA) technique in UAV assisted IoT networks. An antenna selection algorithm is proposed that selects a set of active antennas enabling user fairness. The numerical formulations for the air-to-ground communication links in the S-NOMA system is also obtained. Further, the paper proposes a power consumption model for the S-NOMA enabled network to carry out the energy efficiency analysis. The transmit power consumption, circuit power consumption and UAV hovering power is taken into account. The proposed S-NOMA framework with optimal antenna selection is evaluated against conventional NOMA and random schemes. Simulation results demonstrate that S-NOMA achieves superior performance in terms of data rate and energy efficiency. It is observed that at an SNR of 30 dB, the proposed method with achieves a data rate of 15.2 bps/Hz, outperforming conventional NOMA which achieves 6.4 bps/Hz. Also, the energy efficiency improves by 14.4% at transmit power P=25 dBm with the proposed antenna selection scheme over random selection scheme. This improvement is attributed to the enhanced spatial gain and power-aware antenna selection, thus resulting in sustainable UAV IoT networks.
(Copyright: © 2026 Soni et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The authors have declared that no competing interests exist.