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.