By effectively implementing the strategies for resource allocation, the capabilities, and reliability of non-terrestrial networks (NTN) can be enhanced. This leads to enhance spectrum utilization performance while minimizing the unmet system capacity, meeting quality of service (QoS) requirements and overall system optimization. In turn, a wide range of applications and services in various domains can be supported. However, allocating resources in a multi-constellation system with heterogeneous satellite links and highly dynamic user traffic demand pose challenges in ensuring sufficient and fair resource distribution. To mitigate these complexities and minimize the overhead, there is a growing shift towards utilizing artificial intelligence (AI) for its ability to handle such problems effectively. This calls for the development of an intelligent decision-making controller using AI to efficiently manage resources in this complex environment. In this context, real-world open datasets play a pivotal role in the development of AI models addressing radio control optimization problems. As a matter of fact, acquiring suitable datasets can be arduous. Therefore, this paper identifies pertinent real-world open datasets representing realistic traffic pattern, network performances and demand for fixed and dynamic user terminals, enabling a variety of uses cases. The aim of gathering and publishing the information of these datasets are to inspire and assist the research community in crafting the advance resource management solutions. In a nutshell, this paper establishes a solid foundation of commercially accessible data, with the potential to set benchmarks and accelerate the resolution of resource allocation optimization challenges.

翻译：通过有效实施资源分配策略，可增强非地面网络的性能与可靠性。这有助于在最小化未满足系统容量的同时提升频谱利用效率，满足服务质量要求并实现系统整体优化，进而支持多领域的广泛应用与服务。然而，在具有异构卫星链路及高度动态用户流量需求的混合星座系统中进行资源分配，在确保充分且公平的资源分布方面面临挑战。为缓解这些复杂性并降低开销，利用人工智能处理此类问题的研究日益兴起。这要求开发基于人工智能的智能决策控制器，以高效管理复杂环境中的资源。在此背景下，真实世界开源数据集在开发面向无线电控制优化问题的人工智能模型中发挥着关键作用。事实上，获取合适的训练数据集往往困难重重。因此，本文识别了适用于固定与动态用户终端的相关真实世界开源数据集，这些数据集能体现真实的流量模式、网络性能与需求，支持多种应用场景。收集并发布这些数据集信息的目的是启发并助力研究社区构建先进的资源管理解决方案。总之，本文为可商业获取的数据建立了坚实基础，有望设定基准并加速资源分配优化难题的解决进程。