Integrating terrestrial and non-terrestrial networks has emerged as a promising paradigm to fulfill the constantly growing demand for connectivity, low transmission delay, and quality of services (QoS). This integration brings together the strengths of terrestrial and non-terrestrial networks, such as the reliability of terrestrial networks, broad coverage, and service continuity of non-terrestrial networks like low earth orbit (LEO) satellites. In this work, we study a data service maximization problem in an integrated terrestrial-non-terrestrial network (I-TNT) where the ground base stations (GBSs) and LEO satellites cooperatively serve the coexisting aerial users (AUs) and ground users (GUs). Then, by considering the spectrum scarcity, interference, and QoS requirements of the users, we jointly optimize the user association, AUE's trajectory, and power allocation. To tackle the formulated mixed-integer non-convex problem, we disintegrate it into two subproblems: 1) user association problem and 2) trajectory and power allocation problem. Since the user association problem is a binary integer programming problem, we use the standard convex optimization method to solve it. Meanwhile, the trajectory and power allocation problem is solved by the deep deterministic policy gradient (DDPG) method to cope with the problem's non-convexity and dynamic network environments. Then, the two subproblems are alternately solved by the proposed iterative algorithm. By comparing with the baselines in the existing literature, extensive simulations are conducted to evaluate the performance of the proposed framework.

翻译：集成天地网络已成为满足日益增长的连接需求、低传输延迟和服务质量（QoS）要求的一种有前景的范式。这种整合汇聚了天地网络各自的优势，例如地面网络的可靠性，以及低地球轨道（LEO）卫星等非地面网络的广泛覆盖和服务连续性。本文研究集成天地网络（I-TNT）中的数据服务最大化问题，其中地面基站（GBS）与LEO卫星协同服务共存的空间用户（AU）和地面用户（GU）。考虑到频谱稀缺性、用户间干扰及QoS需求，我们联合优化用户关联、AU轨迹和功率分配。为处理这一混合整数非凸问题，我们将其分解为两个子问题：1）用户关联问题；2）轨迹与功率分配问题。由于用户关联问题属于二元整数规划问题，我们采用标准凸优化方法求解。同时，轨迹与功率分配问题通过深度确定性策略梯度（DDPG）方法处理，以应对问题的非凸性和动态网络环境。随后，通过提出的迭代算法交替求解这两个子问题。通过与现有文献中的基线方法进行比较，我们进行了大量仿真以评估所提框架的性能。