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 the reliability of terrestrial networks, broad coverage and service continuity of non-terrestrial networks like low earth orbit satellites (LEOSats), etc. In this work, we study a data service maximization problem in space-air-ground integrated network (SAGIN) where the ground base stations (GBSs) and LEOSats 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, AU'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. We formulate the user association problem as a binary integer programming problem and solve it by using the Gurobi optimizer. 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 block coordinate descent algorithm. By comparing with the baselines in the existing literature, extensive simulations are conducted to evaluate the performance of the proposed framework.

翻译：整合地面与非地面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)要求的可行范式。这种整合结合了地面网络的可靠性优势，以及低地球轨道卫星(LEOSats)等非地面网络的广域覆盖与服务连续性优势。本文研究空天地一体化网络(SAGIN)中的数据服务最大化问题，其中地面基站(GBSs)与LEOSats协同服务共存的空间用户(AUs)和地面用户(GUs)。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轨迹与功率分配。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。我们将用户关联问题建模为二进制整数规划问题，并采用Gurobi优化器求解。同时，为应对问题的非凸性与动态网络环境，采用深度确定性策略梯度(DDPG)方法求解轨迹与功率分配问题。随后，通过提出的块坐标下降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，开展大量仿真实验以评估所提框架的性能。