# A DRL-Based Satellite Service Allocation Method in LEO Satellite Networks
## 1 Introduction
In [27; 28; 29], a correlation strategy of a three-layer architecture that contains the satellite, base station, and user is considered. Another proposal [27] aims to reduce end-to-end delay by developing an iterative algorithm based on approximation and relaxation methods, which solves the optimization problem of association and resource allocation under load balancing and demand constraints of user device. A different solution [28] focuses on the user, searching for base stations with a maximum rate and minimum load and connecting them to the satellite through the best channel quality. In [29], [PERSON] et al. adopted a multi-agent DRL algorithm which sets users, base stations, and satellites as agents. The SI-R based utility function is considered when selecting the access base stations or satellites for users. The sample is be sent to the MADDPG model for training. In [30], the authors propose a satellite-gateway association strategy using the graph-theory approach, where a bipartite graph is established with the weight set from the channel gain and the coverage of satellites. Accordingly, the association solution is obtained by finding the maximum weighted matching. The satellite selection problem is considered as a potential game in [31], where ground user equipment competes for satellite and channel resources. In [32], the authors proposed a multi-objective satellite selection strategy for multiple users based on reinforcement learning. The work by [31; 32] both considers factors such as remaining visible time, terminal-satellite elevation angle, and available channel numbers to assist users in selecting satellites for decision-making. In [33; 34], the GS algorithm is used for initial matching in the user-satellite association/computation offloading subproblem to obtain the user's satellite selection decision results. In the design of the preference list, communication conditions are still the main factor. Although the above papers examine the access satellite selection of users under multi-satellite coverage, most of them only refer to the impact of the communication environment and rarely consider the resource utilization and service satisfaction of users in satellite systems, which is not conducive to the load balancing of the entire satellite-terrestrial integrated network. Some studies have considered the association between users and satellites. The work by [26] proposes a joint client selection and resource allocation strategy for the multi-task joint learning system, which selects satellite nodes based on wireless communication factors and local task data training results. In [27; 28; 29], the authors consider the correlation strategy of the three-layer architecture which contains the satellite, base station, and user. In [27], the authors aim to reduce end-to-end delay by developing an iterative algorithm based on approximation and relaxation methods, which solves the optimization problem of association and resource allocation under load balancing and demand constraints of the user device. The solution described in [28] focuses on the user, searching for base stations which have maximum rate and minimum load and connecting them to the satellite through the best channel quality. In [29], [PERSON] et al. adopted a multi-agent DRL algorithm which sets users, base stations, and satellites as agents. The SINR-based utility function is considered when selecting the access base stations or satellites for users. The sample is sent to the MADDPG model for training. In [30], the authors proposed a satellite-gateway association strategy using the graph-theory approach, where a bipartite graph is established with the weight set from the channel gain and the coverage of satellites. Accordingly, the association solution is obtained by finding the maximum weighted matching. The satellite selection problem is considered as a potential game in [31],where ground user equipment competes for satellite and channel resources.