Deep Q-Learning Aided Networking, Caching, and Computing Resources Allocation in Software-Defined Satellite-Terrestrial Networks

With the development of satellite networks, there is an emerging trend to integrate satellite networks with terrestrial networks, called satellite-terrestrial networks (STNs). The improvements of STNs need innovative information and communication technologies, such as networking, caching, and computing. In this paper, we propose a software-defined STN to manage and orchestrate networking, caching, and computing resources jointly. We formulate the joint resources allocation problem as a joint optimization problem, and use a deep Q-learning approach to solve it. Simulation results show the effectiveness of our proposed scheme.