The Satellite network is an important part of the global network. However, the complex architecture, changeable constellation topology, and frequent inter-satellite connection switching problems bring great challenges to the routing designs of satellite networks, making the study of the routing methods in satellite networks a research hotspot. Therefore, this paper investigates the latest existing routing works to tackle the dynamic routing problems in satellite networks. The architecture and development of satellite networks are presented and analyzed first. Afterward, dynamic routing problems in satellite networks are analyzed in detail based on the time-varying network topology. According to the latest works, the advanced satellite network routing schemes, including single-layer and multi-layer dynamic routing are introduced and analyzed. In addition, the merits, shortcomings, and applications of these schemes are analyzed and summarized. Finally, potential technologies and future directions are discussed.

Low earth orbit mobile satellite system (LEO-MSS) is the major system to provide communication support for the regions beyond the coverage of terrestrial network systems. However, passive handover happens frequently caused by the quick movement of LEO satellites in LEO-MSS. It not only causes the waste of radio resource, but also makes it hard to guarantee the quality of service (QoS), especially for user groups in hot-spot regions. To tackle this problem, we propose an extensible multi-layer network architecture to reduce the handover rate, especially group handover rate by introducing high-altitude platforms (HAPs) and terrestrial relays (TRs) to this system. We then propose a multi-layer handover management framework and also design different handover procedures based on handover forecast for different kinds of handovers according to the proposed architecture and framework to reduce handover delay and signalling cost. Furthermore, we propose a dynamic handover optimization to reduce the dropping probability and guarantee the QoS of mobile terminals. Numerical results show that the proposed architecture reduces group handovers significantly. The proposed handover procedures also provide better performance on delay and signalling cost compared with traditional handover protocols. With the proposed dynamic handover optimization, the proposed handover procedures provide better performance on dropping probability and throughput. The proposed dynamic handover optimization has an excellent performance on dropping probability while guaranteeing the QoS of mobile terminals.

Low earth orbit mobile satellite system (LEO-MSS) is the major system to provide communication support for mobile terminals beyond the coverage of terrestrial communication systems. However, the quick movement of LEO satellites and current single-layer system architecture impose restrictions on the capability to provide satisfactory service quality, especially for the remote and non-land regions with high traffic requirement. To tackle this problem, high-altitude platforms (HAPs) and terrestrial relays (TRs) are introduced to cover hot-spot regions, and the current single-layer system becomes an LEO-HAP multi-layer access network. Under this setup, we propose a hierarchical resource allocation approach to circumvent the complex management caused by the intricate relationships among different layers. Specifically, to maximize the throughputs, we propose a dynamic multi-beam joint resource optimization method in LEO-ground downlinks based on the predicted movement of LEO satellites. Afterwards, we propose the dynamic resource optimization method of HAP-ground downlinks when LEO satellites and HAPs share the same spectrum. To solve these problems, we use the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to find the optimal solutions. Numerical results show that the proposed architecture outperforms current LEO-MSS in terms of average capacity. In addition, the proposed optimization methods increase the throughputs of LEO-ground downlinks and HAP-ground downlinks with an acceptable complexity.

Satellite mobile communication networks can provide communication services in areas beyond the coverage of terrestrial cellular networks. Ground relay stations for satellite networks is an effective solution to improve the coverage quality and to ensure connectivity between regular ground terminals and the satellite network. Without power grid coverage, the ground relay station can only be powered by green energy generation devices. So the problem of energy-saving under sleep strategy is worthy of studying.This paper proposes an energy-saving sleep control method for ground relay stations through Double Deep Q Network (DDQN) algorithm. Based on the traditional rule-based method that is only set for residual energy, it also considers the impact of weather factors on solar and wind power generation on the energy efficiency of relay stations. The research results show that by considering multiple influencing factors at the same time, the method used in this paper can effectively save non-communication energy consumption at low loads, ensure the satellite communication needs of most users, and improve the operational energy efficiency of the relay station over a period of time.

In a relay satellite system, low earth orbit (LEO) satellites are the users of a geosynchronous earth orbit (GEO) satellite, and each highly dynamic GEO-LEO link has a different Doppler shift due to the movement of LEO satellites, which causes serious inter-resource-block(RB) interference and leads to significant degradation of capacity. In this paper, to reduce interRB interference caused by different Doppler shift and maximize the uplink capacity, we derive the mathematical formulae to describe the inter-RB interference with a fixed Doppler shift and propose a resource allocation approach. The problem is formulated as a non-convex optimization model and Lagrangian duality method is used to solve it. Finally, we present a subgradient algorithm to get the results. Simulation results show that the proposed resource allocation method compared to the QPSO (quantum-behaved particle swarm optimization) resource allocation algorithm has a better capacity after decreasing interRB interference.

Equipped with solar energy and wind energy supply, satellite ground relay stations (SGRS) can be deployed in remote regions without the support of a ground power network to provide communication access for ordinary mobile terminals in satellite mobile communications networks. Due to the instability and limitation of solar energy and wind energy supply, reducing energy consumption and improving the energy-efficiency of SGRS is very important. Focusing on the unstable and limited energy problem on SGRS, this article proposes a soft actor–critic-based joint resource allocation (SAC-JRA) algorithm to improve the transmission energy-efficiency of SGRS. The proposed SAC-JRA algorithm includes a multidimensional state space, a hierarchical action space, and a dual-weight reward function to balance energy-efficiency and user satisfaction. A lightweight dual-branch neural network is used to decouple power and bandwidth allocation, enhancing decision-making efficiency and adaptability. Simulation results demonstrate that the proposed SAC-JRA algorithm achieves significant improvements in transmission energy-efficiency compared with existing methods, especially in low traffic load and mixed traffic load environments. The results also show the robustness of the proposed SAC-JRA algorithm in dynamic traffic loads, offering a sustainable solution for energy-constrained wireless communications.