Probabilistic-aware satellite constellation scheduling for integrated TN-NTN operations
The integration of satellite-based Non-Terrestrial Networks (NTN) with terrestrial communication infrastructures introduces significant challenges, especially in coping with the unpredictable nature of traffic generated by end users. Traditional scheduling approaches in satellite systems often assum...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/433570 |
| Acceso en línea: | https://hdl.handle.net/2117/433570 https://dx.doi.org/10.1109/OJCOMS.2025.3564411 |
| Access Level: | acceso abierto |
| Palabra clave: | Satellite constellation Non-terrestrial networks TN-NTN integration Uncertainty modeling Operations management Àrees temàtiques de la UPC::Enginyeria electrònica::Microelectrònica |
| Sumario: | The integration of satellite-based Non-Terrestrial Networks (NTN) with terrestrial communication infrastructures introduces significant challenges, especially in coping with the unpredictable nature of traffic generated by end users. Traditional scheduling approaches in satellite systems often assume deterministic traffic models, limiting their effectiveness in dynamic and data-driven scenarios. This paper presents a framework for integrated NTN operations that incorporates stochastic traffic modeling into satellite scheduling, enabling a more flexible and realistic approach to resource management in NTNs. By leveraging statistical traffic models based on the central limit theorem, the proposed method accounts for traffic uncertainty and embeds it directly into the scheduling process. A key concept introduced is schedule certainty, which quantifies the reliability of a schedule under uncertain input conditions and serves as both a decision variable and an optimization parameter. This novel approach is exemplified through the Constellation Management System framework, extended with a data generation uncertainty model to showcase its practical implementation and benefits. Results demonstrate that probability-aware scheduling achieves a tightly controlled certainty level aligned with operator-defined thresholds, providing higher certainty levels for equivalent performance metrics. This allows satellite operators to dynamically adjust service coverage and system efficiency, accounting for varying levels of traffic uncertainty. This work highlights the importance of probability-aware scheduling in enabling more robust and efficient operation of future satellite-terrestrial hybrid networks. |
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