Towards Resilient and Secure Beyond-5G Non-Terrestrial Networks (B5G-NTNs): An End-to-End Cloud-Native Framework

Integrating Terrestrial and Non-Terrestrial Networks (NTNs) within Beyond-5G (B5G) and future 6G ecosystems represents a transformative advancement in achieving ubiquitous, resilient, and scalable communication services. NTNs, including Low Earth Orbit (LEO) satellites, Unmanned Aerial Vehicles (UAVs), and High Altitude Platform Systems (HAPS), extend traditional terrestrial networks by providing continuous connectivity in remote, underserved, and connection-critical scenarios such as disaster-hit regions and rural areas. This thesis deals with an end-to-end cloud-native framework that leverages cutting-edge technologies, including Multi-Access Edge Computing (MEC), Software Defined Networking (SDN), Network Function Virtualization (NFV), blockchain, and advanced AI/ML models, to enhance service availability, security, and Quality of Service (QoS) in 3D NTN environments. The research first explores the deployment of disaggregated Next-Generation Radio Access Networks (NGRANs) across terrestrial and non-terrestrial domains using a Kubernetes-based architecture. A Graph Neural Network (GNN) model is developed to monitor and manage these networks, detecting link failures and optimizing traffic routing paths between terrestrial and satellite components. The GNN model achieves an 85% accuracy in link failure detection and significantly reduces end-to-end delays in NTN deployments, highlighting the potential of AI-driven network management in enhancing overall network resilience. To address the challenge of dynamic resource management in NTNs, this thesis investigates the implementation of functional splits, such as F1 and E1 interfaces, between terrestrial control units (gNB-CU) and satellite-based distributed units (gNB-DU). The study employs Long Short-Term Memory (LSTM) neural networks to predict resource utilization, specifically CPU, memory, and bandwidth of satellite payloads. These predictive models enable proactive monitoring and resource allocation decisions, ensuring efficient use of limited computational resources and maintaining high levels of network performance. Security remains a critical concern in NTNs due to decentralized and open 5G satellite communications. A blockchain-based authentication framework is proposed to mitigate these risks, enhancing the security of data exchanges and remote firmware updates in LEO satellite constellations. Blockchain technology provides a decentralized, transparent, and immutable security framework, improving authentication efficiency and protecting against unauthorized access, though with trade-offs in network performance, such as increased latency and reduced throughput. This approach makes the hybrid B5G NTN network secure, reinforcing the integrity and confidentiality of communication channels, which is essential for emerging services and applications. Furthermore, this thesis comprehensively evaluates MEC-based experimental testbeds that demonstrate service resiliency in NTNs during terrestrial network outages. The MEC deployments allow seamless transitions to satellite access networks, ensuring service continuity and improving QoS. These testbeds showcase the capability of cloud native technologies in maintaining service availability, highlighting their critical role in resilient NTN networks. The findings of this thesis demonstrate that integrating cloud-native architectures, blockchain-based security mechanisms, and advanced AI/ML models significantly enhances the resilience, security, and resource efficiency of NTNs. These innovations pave the way for robust, adaptive, and secure communication systems, supporting the seamless deployment of critical B5G and 6G applications across diverse and challenging environments. This research provides valuable insights into designing and implementing resilient NTNs, setting the foundation for future advancements in global connectivity and intelligent network management.