Mobile users such as airplanes or ships will constitute an important segment of the future satellite communications market. Operators are now able to leverage digital payloads that allow flexible resource allocation policies that are robust against dynamic user bases. One of the key problems is managing the frequency spectrum efficiently, which has not been sufficiently explored for mobile users. To address this gap, we propose a dynamic frequency management algorithm based on linear programming that assigns resources in scenarios with both fixed and mobile users by combining long-term planning with real-time operation. We propose different strategies divided into proactive strategies, which stem from robust optimization practices, and reactive strategies, which exploit a high degree of real-time control. This represents a tradeoff between how conservative long-time planning should be and how much real-time reconfiguration is needed. To assess the performance of our method and to determine which proactive and reactive strategies work better under which context, we simulate operational use cases of non-geostationary constellations with different levels of dimensionality and uncertainty, showing that our method is able to serve over 99.97\% of the fixed and mobile users in scenarios with more than 900 beams. Finally, we discuss the trade-offs between the studied strategies in terms of the number of served users, power consumption, and number of changes that need to happen during operations.

翻译：飞机或船舶等移动用户将成为未来卫星通信市场的重要部分。运营商现可利用数字有效载荷实现灵活的资源分配策略，以应对动态用户群体的挑战。其中关键问题之一是如何高效管理频谱资源，而针对移动用户的这一领域尚未得到充分探索。为填补这一空白，我们提出一种基于线性规划的动态频率管理算法，通过结合长期规划与实时操作，在同时包含固定用户和移动用户的场景中进行资源分配。我们提出不同策略，分为源自鲁棒优化实践的主动策略和利用高实时控制能力的响应式策略。这体现了长期规划的保守程度与实时重构需求之间的权衡。为评估方法性能并确定不同场景下主动策略与响应式策略的适用性，我们模拟了具有不同维度与不确定性的非静止轨道星座运行用例，结果显示在包含900余个波束的场景中，该方法能为超过99.97%的固定和移动用户提供服务。最后，我们从服务用户数、功耗及操作期间所需变更次数等方面，讨论了所研究策略间的权衡关系。