In this work, we propose an adaptive system design for an Internet of Things (IoT) monitoring network with latency and reliability requirements, where IoT devices generate time-critical and event-triggered bursty traffic, and an unmanned aerial vehicle (UAV) aggregates and relays sensed data to the base station. Existing transmission schemes based on the overall average traffic rates over-utilize network resources when traffic is smooth, and suffer from packet collisions when traffic is bursty which occurs in an event of interest. We address such problems by designing an adaptive transmission scheme employing multiuser shared access (MUSA) based grant-free non-orthogonal multiple access and use short packet communication for low latency of the IoT-to-UAV communication. Specifically, to accommodate bursty traffic, we design an analytical framework and formulate an optimization problem to maximize the performance by determining the optimal number of transmission time slots, subject to the stringent reliability and latency constraints. We compare the performance of the proposed scheme with a non-adaptive power-diversity based scheme with a fixed number of time slots. Our results show that the proposed scheme has superior reliability and stability in comparison to the state-of-the-art scheme at moderate to high average traffic rates, while satisfying the stringent latency requirements.

The consideration of unmanned aerial vehicle (UAV) trajectory is of crucial importance in the performance evaluation of cellular-connected UAV networks. In this work, we consider a cellular-connected aerial user equipment (AUE) employed for surveillance and monitoring. The AUE moves along a given trajectory, while periodically transmitting to a terrestrial base station (BS) in the uplink, with a specific quality of service (QoS) requirement. To avoid the underutilization of spectrum resources, we enable simultaneous uplink transmissions of the AUE and a terrestrial user equipment (TUE) using power-domain uplink aerial-terrestrial non-orthogonal multiple access (NOMA). We take the trajectory of AUE into consideration and develop an analytical framework to compute the total rate coverage probability, i.e., the probability where both AUE and TUE are decoded, at a given transmission point in the trajectory. In addition, we numerically determine the minimum height of AUE to achieve a certain QoS constraint for different AUE target data rates and built-up areas. Our results show that, for a spiral trajectory, the minimum height increases as the AUE moves from cell center to the boundary, and as the severity of the environmental parameters increases.

This paper considers an emerging cellular-connected unmanned aerial vehicle (UAV) architecture for surveillance or monitoring applications. We study a scenario of interest where a cellular-connected aerial user equipment (AUE) periodically transmits in uplink to a base station (BS) with a given data rate requirement, while moving along a given trajectory. For an efficient spectrum usage, we enable the concurrent uplink transmission of the AUE and a terrestrial user equipment (TUE) by employing power-domain aerial-terrestrial non-orthogonal multiple access (NOMA), while accounting for the AUE's known trajectory. To characterize the system performance, we develop an analytical framework to compute the rate coverage probability, i.e., the probability that the achievable data rate of both the AUE and TUE exceeds the respective target rates. We use our analytical results to numerically determine the minimum height that the AUE needs to fly, at each transmission point along the given trajectory, in order to satisfy a certain quality of service (QoS) constraint of various AUE target data rates in different built-up environments. Specifically, our results show that the minimum height of the AUE depends on its distance from the BS as the AUE moves along the given trajectory which indicates the importance of modeling AUE trajectory in cellular-connected UAV systems.