Resource slicing in low Earth orbit satellite networks (LSN) is essential to support diversified services. In this paper, we investigate a resource slicing problem in LSN to reserve resources in satellites to achieve efficient resource provisioning. To address the challenges of non-stationary service demands, inaccurate prediction, and satellite mobility, we propose an adaptive digital twin (DT)-assisted resource slicing scheme for robust and adaptive resource management in LSN. Specifically, a slice DT, being able to capture the service demand prediction uncertainty through collected service demand data, is constructed to enhance the robustness of resource slicing decisions for dynamic service demands. In addition, the constructed DT can emulate resource slicing decisions for evaluating their performance, enabling adaptive slicing decision updates to efficiently reserve resources in LSN. Simulation results demonstrate that the proposed scheme outperforms benchmark methods, achieving low service demand violations with efficient resource consumption.

翻译：低地球轨道卫星网络中的资源切片对于支持多样化服务至关重要。本文研究低轨卫星网络中的资源切片问题，通过在卫星中预留资源以实现高效资源供给。为应对非平稳服务需求、预测不准确及卫星移动性等挑战，我们提出一种自适应数字孪生辅助的资源切片方案，用于实现低轨卫星网络中鲁棒自适应的资源管理。具体而言，通过构建能够基于收集的服务需求数据捕捉需求预测不确定性的切片数字孪生，增强动态服务需求下资源切片决策的鲁棒性。此外，所构建的数字孪生可模拟资源切片决策以评估其性能，从而实现自适应切片决策更新，在低轨卫星网络中高效预留资源。仿真结果表明，所提方案优于基准方法，在实现高效资源消耗的同时保持较低的服务需求违规率。