Aerial link orchestration

Abstract

Unmanned Aerial Vehicles (UAVs) have become indispensable tools due to their superior maneuverability and flexibility in a variety of activities such as mapping, infrastructure monitoring, and object tracking. Their applications are many, ranging from industrial and military surveillance to commercial delivery and other operations. Because of their hardware architectures, atmospheric factors such as wind and turbulence restrict the movement of UAVs, particularly drones. These conditions not only interfere with their responsiveness but also limit the operation of integrated systems and communication between the drone and the ground control station (GCS). It is critical in drone operations to maintain communication systems with the GCS and ensure the correct functioning of integrated systems, including managing the drone's movement parameters. These different uses, as well as the associated environmental circumstances, highlight the crucial requirement for UAVs to function dependably, as well as the importance of suitable regulations and adaptations. Drones and UAVs utilize a variety of communication methods in order to create a data link between the vehicle and GCS and sometimes between multiple aircraft (swarm technology). UAV communication systems can be utilized for data and image transmission from sensors and payloads to the control station, broadcasting telemetry systems, and command and control. Additionally, they provide bidirectional communication from air to ground and ground to air by allowing data and commands to be received at the ground station. The most common ways of drone communication employ radio-frequency (RF) signals in bands such as HF (high frequency) , satellites, cellulars, and other wireless infrastructures. However, radio technologies are the most widely used. RF datalinks can be analog or digital and have a longer range than Wi-Fi, although they are still limited to line-of-sight (LOS). The range of the UAV communications system is determined by the direction and size of the antenna, the strength of the transmitter, and the frequency, with lower frequencies allowing longer ranges but lower data rates. By addressing these technical difficulties, we develop new techniques to improve UAV communication quality and identify drone flight parameters that influence communication quality. Our goal is to create communication systems that are less impacted by these elements. Our research aims to overcome constraints in high-frequency transmission imposed by drone instability and antenna limitations. Our primary goal is to provide safe, continuous communication while greatly increasing the packet delivery ratio (PDR). We create resilient and adaptive UAV systems that can function well in a variety of dynamic operational scenarios by taking advantage of the inherent flexibility of Software Defined Radio (SDR) technology. This holistic approach encompasses proactive measures against signal interference, noise mitigation, and the management of flight-induced vibrations, harnessing SDR's configurability to meet the evolving demands of modern UAV operations effectively. Our approach involves: * Addressing Drone Flight Patterns and Aerial Conditions: We classify different aerial conditions affecting UAVs. *Enhancing the Modulation and Coding Scheme (MCS): We improve the MCS table to be aware of aerial and flight conditions. *Exhaustive Real-World Experimentation: Utilizing a "train on day, test on the next day" methodology on a real test bed. To increase drone PDR, we use Digital Twin architecture to detect influential parameters. Using the "train one day, test another day" method, we include real-world test flight log data from drones and SDR communication attributes into our digital twin model. This allows us to discover the best parameter values for getting a high PDR, which we then feed back into our system. Based on these results, we update the existing static MCS table to reflect the effect of the identified drone flying factors on communication performance. Our results validated methodologies have demonstrated significant improvements in PDR, achieving an average increase of 27\% across multiple drone platforms and environmental scenarios. These findings underscore the effectiveness of our approach in optimizing communication performance under real-world conditions. Furthermore, our research provides valuable insights into the intricate interactions between UAV flight dynamics and communication efficacy, guiding future advancements in UAV technology. In summary, our research underscores the critical importance of maintaining robust communication networks in dynamic UAV environments. By proposing and validating innovative methodologies, we lay the groundwork for enhanced UAV communication resilience and efficiency. Future endeavors will build upon these foundations, expanding system capabilities across broader operational scenarios and pushing the boundaries of UAV communication technology to new heights.