Time Synchronization and Packet Scheduling for Satellite LoRaWAN Networks

The convergence of satellite networks and Internet of Things (IoT) technologies offers transformative solutions for enhancing connectivity in remote and underserved regions where traditional network and power infrastructure are lacking. Despite the potential of LoRaWAN-a widely adopted communication protocol for IoT due to its low energy consumption, extended communication range, and cost-efficiency-its integration with Low Earth Orbit (LEO) satellite systems presents critical technical challenges. Limited satellite visibility leads to intermittent connectivity, while high device density during satellite visibility periods results in data collisions and communication failures, affecting network performance and scalability. Addressing these issues is imperative to unlock the full potential of satellitesupported IoT networks for applications ranging from environmental monitoring to disaster response in hard-to-reach areas. This Ph.D. Thesis introduces two novel frameworks for satellite LoRaWAN systems: REACT (LoRaWAN differential time synchronization) and SALSA (Scheduling Algorithm for LoRa to LEO Satellite). REACT tackles the challenge of temporal misalignment by enabling precise synchronization between IoT devices and satellite visibility windows, optimizing data transmission opportunities. SALSA addresses packet collisions and congestion by implementing an intelligent scheduling algorithm that enhances network throughput and reliability. The proposed solutions underwent extensive validation through simulations and real-world testbed deployments across diverse geographical regions and under multiple LEO satellite constellation configurations. This multi-scenario evaluation demonstrates the generalizability of the proposed frameworks, confirming their robustness, adaptability, and effectiveness in improving transmission efficiency, scalability, and overall network performance under varying satellite orbits.