A Study on Connectivity and Delay in NTN Assisted Vehicular Networks

Abstract

Non-Terrestrial Networks (NTNs) offer a transformative solution for sustaining connectiv- ity in Vehicular Data Networks (VDNs), where intelligent transportation services demand persistent, low-latency communications. While Unmanned Aerial Vehicles (UAVs) pro- vide mobility and rapid deployment advantages for intermittently connected vehicular scenarios, UAV-only deployments face critical limitations, including coverage variability, operational constraints, and inadequate performance under sparse traffic and fragmented network topologies. This thesis addresses these challenges by proposing and analyz- ing a unified Vehicle–UAV–HAP (High-Altitude Platform) hierarchical architecture that exploits the complementary strengths of these tiers. UAVs enable agile, localized con- nectivity restoration, whereas HAPs provides persistent wide-area coverage to mitigate sustained connectivity gaps. Free-flow traffic conditions, characterized by large inter- vehicle spacing and frequent network partitions, constitute the primary operating regime of interest. A comprehensive analytical and simulation framework is developed to model the spatiotemporal dynamics of the proposed multi-tier system. The framework quantifies key Quality-of-Service (QoS) metrics, including connectivity probability, path availabil- ity, and end-to-end delay, under realistic vehicular mobility patterns. Although satellite networks can extend coverage further, prohibitive operational costs often limit near-term feasibility. Accordingly, HAPS is positioned as a cost-effective solution for enhancing net- work availability, with satellites serving as a longer-term complementary technology. The results provide deployment-oriented guidelines for tier selection, resource dimensioning, and system optimization in NTN-enabled intermittently connected vehicular networks, strengthening the link between theoretical modeling and practical implementation.