Low altitude unmanned aerial vehicles (UAVs) in wireless networks

Abstract

In the realm of 5G wireless communications, UAVs present an intriguing prospect owing to their inherent attributes, such as mobility, flexible deployment, autonomy, line-of-sight establishment, and adjustable altitude. The rapid evolution of 5G and beyond 5G networks, alongside advancements in miniaturization, control, computerization, and cost reduction in UAV manufacturing, has propelled UAVs into pivotal roles across industrial, commercial, and civilian domains. Within this context, this thesis focuses on three distinct UAV applications: firstly, the utilization of cellular-connected UAVs as aerial users; secondly, the deployment of a UAV as an aggregator to increase communication range and increase reliability of an Internet of Things networks with high reliability and low latency requirements; and thirdly, their integration into maritime-satellite networks to enable communication between maritime users and satellites, in the absence of onshore base stations.

Firstly, we explore a novel cellular-connected UAV architecture tailored for surveillance or monitoring applications. We investigate a specific scenario wherein a cellular-connected aerial user equipment (AUE) periodically transmits data in the uplink, adhering to a predetermined data rate requirement while traversing a predefined trajectory. For efficient spectrum utilization, we introduce power-domain aerial-terrestrial non-orthogonal multiple access (NOMA), allowing simultaneous uplink transmission of both the AUE and a terrestrial user equipment (TUE) while considering the AUE's known trajectory. To evaluate system performance, we establish an analytical framework for computing the rate coverage probability, which signifies the likelihood of achieving the target data rates for both the AUE and TUE.

Next, we present an adaptive system design tailored for an Internet of Things (IoT) monitoring network characterized by stringent latency and reliability prerequisites. In this network paradigm, IoT devices generate bursty, time-critical, and event-triggered traffic, while a UAV is deployed for aggregating and relaying sensed data to the base station. Conventional transmission schemes, predicated on overall average traffic rates, tend to overburden network resources during periods of smooth traffic flow and are susceptible to packet collisions during bursts of activity, such as events of interest. To mitigate these challenges, we propose an adaptive transmission scheme leveraging multiuser shared access (MUSA) through grant-free non-orthogonal multiple access, alongside employing short packet communication to ensure low-latency IoT-to-UAV communication. Specifically, to adeptly handle bursty traffic patterns, we develop an analytical framework and formulate an optimization problem aimed at maximizing performance by determining the optimal number of transmission time slots, while adhering to stringent reliability and latency constraints.

Finally, we investigate a UAV-assisted maritime-satellite communication network, wherein low-end maritime users (MUs) dispersed across a finite oceanic area establish communication with Low Earth Orbit (LEO) satellites via a swarm of UAV relays positioned within a finite aerial domain. We introduce a two-phase communication approach, wherein a reference UAV situated at an arbitrary location is served by its nearest MU in the MU-to-UAV communication phase, followed by relaying the received data to the closest satellite in the UAV-to-satellite communication phase. To analyze performance, we develop a location-dependent UAV-centric analytical framework, employing finite area stochastic geometry and success probability as the primary performance metric. Show more