## 1 Introduction  
As the global mobile industry progresses towards the era of 6G networks, satellite networks are increasingly emerging as a primary competitive technology for delivering ubiquitous communication services worldwide. These satellite networks serve as a valuable complement to terrestrial infrastructure, offering an extensive coverage area and ensuring system fault tolerance. This resilience enables users to maintain connectivity in remote regions or during natural disasters when terrestrial communication may be unavailable. Additionally, satellite networks facilitate the integration of cutting-edge technologies such as Artificial Intelligence, IoT, Big Data, and others, enabling the provision of a diverse range of services. When compared to Wi-Fi, Bluetooth, and traditional cellular networks, satellite networks possess distinct advantages for remote facility monitoring and real-time asset management across vast geographical expanses. Currently, satellite communication networks have found application in global communication, high-precision navigation and positioning (e.g., Bei Dou Navigation Satellite System), remote sensing, and various other scenarios. These applicationsserve as compelling evidence of the effectiveness and full capability of utilizing satellite networks for communication and data transmission interactions. In satellite networks, an ingress satellite gathers data from terminals and forwards it to destination terminals through egress satellites. Satellite networks offer a convenient solution for terminal devices located in remote areas lacking stable terrestrial broadband infrastructure, granting them easy access to the cloud. Likewise, cloud operators can effortlessly distribute new configurations and tasks to distributed terminal devices, regardless of location or time [1]. Efficient data transmission in satellite networks relies heavily on an effective routing scheme. Nevertheless, on a global scale, traffic requirements within satellite networks are often unevenly distributed. Satellites covering developed regions generally handle heavier traffic loads compared to those covering underdeveloped areas, oceans, or mountainous regions [2]. Furthermore, when traditional shortest path routing algorithms are employed, irregular constellation structures and varying inter-satellite link (ISL) lengths can lead to traffic congestion in specific areas. Furthermore, the issues related to communication performance, energy efficiency, and security in integrated satellite and ground terminal networks have also sparked discussions among scholars [3; 4; 5]. Given the limited bandwidth resources typically available from satellites, these factors can quickly result in severe congestion and significant packet drops in certain satellites while leaving others underutilized. Hence, the implementation of rational and effective resource allocation mechanisms, taking into account satellite bandwidth resources and dynamic traffic demands, becomes crucial for meeting user service requirements. Resource allocation directly impacts the operational costs of satellite networks and the user experience of IoT devices. An irrational allocation of resources not only increases communication network operating costs but can also lead to substantial energy wastage. Accurately predicting network traffic trends offers an insightful representation of shifting service demands. The precision of prediction outcomes is paramount for achieving a well-balanced allocation of network resources, optimizing the distribution of existing satellite resources, and efficiently offloading computing tasks [6; 7]. Consequently, establishing a high-precision traffic prediction model for satellite networks holds significant practical importance. Analyzing the distribution and forecasting the demand for communication traffic to guide the allocation of communication resources has consistently been a significant research area [1]. Traditional approaches for wireless traffic prediction have typically relied on manual and statistical methods.