Optimizing Integrated Terrestrial and Non-Terrestrial Networks Performance with Traffic-Aware Resource Management
<|reference_start|>Optimizing Integrated Terrestrial and Non-Terrestrial Networks Performance with Traffic-Aware Resource Management: To address an ever-increasing demand for ubiquitous high-speed connectivity, mobile networks have intensified their deployment process. However, achieving this target has proven to be a challenge and has led to a surge in overall energy consumption. In recent years, non-terrestrial networks (NTNs) have been endorsed as a potential solution to these problems by complementing the coverage of the terrestrial network in areas with limited network deployment. To this end, this paper proposes an integrated terrestrial and non-terrestrial network (TN-NTN) that utilises the overall available communication resources to expand coverage and meet Quality of Service (QoS) requirements during high-traffic hours in any deployment scenario. Importantly, our framework allows to drastically reduce the terrestrial network energy consumption during low-traffic hours. Specifically, we introduce a novel radio resource management algorithm, BLASTER (Bandwidth SpLit, User ASsociation, and PowEr ContRol), which integrates bandwidth allocation, user equipment (UE) association, power control, and base station activation within the TN-NTN. This algorithm aims to optimize network resource allocation fairness and energy consumption dynamically, demonstrating new opportunities in deploying satellite networks in legacy cellular systems. Our study offers a comprehensive analysis of the integrated network model, emphasizing the effective balance between energy saving and QoS, and proposing practical solutions to meet the fluctuating traffic demands of cellular networks.<|reference_end|>
@article{alam2024optimizing,
    title={Optimizing Integrated Terrestrial and Non-Terrestrial Networks
  Performance with Traffic-Aware Resource Management},
    author={Henri Alam, Antonio de Domenico, David L'opez-P'erez, Florian
  Kaltenberger},
    journal={arXiv preprint arXiv:2410.06700},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.06700},
    primaryClass={cs.NI}
}