  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.
