DYNAMIC RESOURCE ALLOCATION FOR NEXT-GENERATION NONTERRESTRIAL NETWORKS

Abstract

The rapid evolution of wireless communication technologies has accelerated the development of NextGeneration Non-Terrestrial Networks (NTNs), which integrate satellites, high-altitude platform systems (HAPS), unmanned aerial vehicles (UAVs), and terrestrial infrastructures to provide seamless global connectivity. NTNs play a crucial role in extending network coverage to remote, rural, maritime, and disaster-affected regions where terrestrial communication infrastructure is limited or unavailable. However, the highly dynamic nature of NTN environments, characterized by varying user demands, mobility patterns, channel conditions, and limited spectrum resources, creates significant challenges in resource management. Dynamic Resource Allocation (DRA) has emerged as a critical solution for optimizing the utilization of communication resources while maintaining Quality of Service (QoS), minimizing latency, and maximizing network throughput. This study presents a dynamic resource allocation framework for next-generation NTNs that intelligently distributes bandwidth, power, and computational resources based on real-time network conditions. The proposed approach incorporates adaptive scheduling, traffic-aware optimization, and predictive analytics to enhance resource efficiency and service reliability. Simulation-based evaluations demonstrate that the dynamic allocation strategy significantly improves spectrum utilization, reduces congestion, and enhances overall network performance compared to conventional static allocation methods. The framework supports scalable and sustainable NTN operations, making it a promising solution for future global communication ecosystems.