Abstract:
n an unmanned aerial vehicle (UAV)-enabled Internet of Thing (IoT) network, the transmission rate of an IoT node
from the aerial base station (ABS) is determined by the signalto-noise ratio (SNR). In general, the characterization of the ABSto-node (A2N) channel is determined by its instantaneous SNR.
The previous works reported in this direction have considered
the average SNR. This study fills the gap in understanding
how fading affects the network’s performance. In this paper,
we consider a UAV-enabled IoT network, where multiple ABSs
are deployed to serve the IoT nodes. We model the A2N channel
based on the instantaneous channel; we consider a generalized
fading model, the Nakagami-m model for the A2N link, to
provide a more generic analysis. Through analytical insights, we
obtain the exact and closed-form approximate expression of the
association probability of IoT node with the ABS and infer the
capacity enhancement obtained by considering fading compared
to the average SNR scenario. The average improvement in
ergodic capacity is around 10% compared to the average fading
scenario. Furthermore, the results show that considering fading
is beneficial for low-altitude scenarios, as it provides a significant
increase in the node association probability compared to the
average fading scenario.
