最新刊期
卷 6 ， 期 4 ， 2025
- 摘要：Space-air-ground integrated networks (SAGIN) establish a multi-dimensional communication architecture by synergistically coordinating satellites, aerial platforms, and terrestrial facilities. The inherent characteristics of dynamic topologies and heterogeneous computing resources within this architecture present novel challenges for routing mechanisms. In response to this complex scenario, reinforcement learning (RL) has emerged as a prominent research focus for addressing computing-aware routing problems, owing to its robust environmental adaptability and intelligent decision-making capabilities. This paper systematically reviews and investigates the application of RL in computing-aware routing. It analyzes the core design principles from the dual perspectives of algorithmic paradigms and optimization objectives. Finally, this paper deeply analyzes and prospectively identifies the key challenges that RL faces in the context of SAGIN environments.关键词：space-integrated-ground;computing power routing;reinforcement learning170|133|0更新时间：2026-01-09
- 摘要：The space-based computing power networks (S-CPN) achieve the connectivity and unified scheduling of on-board computing resources through the networking of computing nodes. This enables the efficient processing of on-board computing tasks, demonstrating significant application potential and theoretical research value.This paper provides a systematic review of the key technologies of S-CPN. Firstly, the concept, current status, and main challenges of S-CPN are systematically summarized. Subsequently, three critical technologies of S-CPN are analyzed in detail: network architecture, computing power measurement and routing, and computing task offloading optimization, along with their research progress and existing challenges. Finally, the future research directions of S-CPN are prospected.关键词：space-based computing power networks;network architecture;computing power measurement;computing power routing;computing task offloading191|129|0更新时间：2026-01-09
Reviews
- 摘要：With the continuous emergence of new technologies and the explosive growth of global Internet demand, the deployment of commercial low earth orbit (LEO) satellite systems has become a key issue in current development. To provide scientific design basis and system-level verification and evaluation plan for the rolling construction of future LEO Internet constellations, and to effectively reduce the additional construction costs caused by technical bottlenecks and system risks, a low-cost, high-fidelity LEO Internet system link performance simulation modeling design method is desigaed, which can verify whether the system can achieve the global seamless coverage link performance target by inputting parameters such as constellation scale, on-board equipment performance, terminal deployment and access capability.关键词：LEO internet constellation;system simulation modeling design;link performance analysis119|186|0更新时间：2026-01-09
- 摘要：To address the NP-hard problem of remote sensing satellite mission planning, this paper proposes a novel gravitational genetic search algorithm (GGSA). This algorithm integrates the rapid convergence capability of the gravitational search algorithm (GSA) with the global exploration strength of the genetic algorithm (GA), and optimizes the solution process through a three-phase hybrid strategy (gravitational search, elite crossover, and directional mutation). At the theoretical level, convergence proof and complexity analysis O(T×N×(P+N×D)) are provided. At the application level, the algorithm's suitability for deployment conditions involving low earth orbit (LEO) optical remote sensing satellites is clarified. Simulation results across six distinct scenario types demonstrate that GGSA exhibits superior capability in handling complex remote sensing satellite mission planning problems, achieving significant advantages in both convergence speed and search accuracy.关键词：remote sensing satellite mission planning;genetic mutation;gravitational search;hybrid strategy;directional mutation64|84|0更新时间：2026-01-09
- 摘要：Satellite networks, with their global coverage advantages, play a crucial role in supporting 6G networks. The integration of mobile edge computing into low earth orbit satellite constellations can provide ground users with low-latency and highly reliable services. Considering the randomness of ground user demands and the heterogeneity of satellite resources, which lead to imbalanced satellite workloads, the task allocation problem is formulated as a mathematical optimization model to ensure a reasonable distribution of satellite tasks. Furthermore, an improved glowworm algorithm is designed to obtain the optimal solution. Comparative evaluations with benchmark algorithms, the effectiveness of the proposed approach has been validated through simulations.关键词：satellite edge computing;task offloading;workload balance;glowworm algorithm78|99|0更新时间：2026-01-09
- 摘要：In order to solve the problem of unbalanced link resource utilization and difficult quality of service guarantee in current low earth orbit satellite networks, a software-defined low earth orbit satellite network traffic load balancing algorithm based on ant colony optimization, namely dynamic load balancing ant colony algorithm, is proposed. This algorithm acquires real-time link information of the satellite network through the software defined network architecture, designs comprehensive path weight parameters according to the QoS requirements of the service, optimizes the pheromone update rules of the ant colony algorithm based on the current link states, updates the pheromones of the ant colony algorithm in real time, calculates the optimal path of the satellite network based on the optimized pheromones and transition probabilities, and sends it to each satellite node. Simulation experiments are conducted under three traffic scenarios of local light load, local medium load and local congestion, and under different scales of low earth orbit satellite constellation scales, this algorithm was compared with Dijkstra optimization and ant colony algorithm. The results show that this algorithm significantly improves the load balancing capability of low earth orbit satellite networks while meeting the quality of service requirements and avoiding network congestion.关键词：low earth orbit satellite networks;ant colony algorithm;load balancing;QoS optimization72|40|0更新时间：2026-01-09
- 摘要：With the development of 6G communication technology, LEO satellite Internet has become a key technology for constructing space-terrestrial integrated networks due to its advantages of global coverage and low latency. However, 6G satellite Internet systems face multi-level strongly coupled decision-making problems such as constellation configuration, resource scheduling, and service optimization, and existing single-layer optimization methods are difficult to effectively handle inter-layer dependencies. To address this issue, a multi-level intelligent decision optimization framework for 6G satellite Internet is proposed. First, a three-layer decision model covering constellation deployment, resource scheduling, and service optimization is constructed, and inter-layer information interaction and constraint transfer mechanisms are established. Then, a hybrid intelligent algorithm based on improved genetic algorithm, convex optimization decomposition, and multi-agent deep reinforcement learning is designed, and multi-level coordinated optimization is achieved through alternating direction method of multipliers. Finally, the framework performance is verified based on MATLAB simulation platform. Experimental results show that compared with traditional hierarchical optimization and heuristic algorithms, the framework improves system capacity, spectrum efficiency, and QoS satisfaction by (8.6±1.2)%, (10.8±1.3)%,and (6.5±0.8)%, respectively.关键词：6G satellite Internet;multi-level decision making;intelligent optimization;resource scheduling;deep reinforcement learning64|77|0更新时间：2026-01-09
- 摘要：This paper proposes an AI-predicted driven hierarchically-coordinated QoS (AIP-HC-QoS) architecture for LEO Walker constellation. The architecture employs an AI engine in the ground intelligence and control center (GICC) for link quality and service demand prediction, while deep reinforcement learning optimizes global QoS and dynamic network slicing. Lightweight intelligent agents are deployed on satellite nodes for local QoS execution. This paper details the system architecture, key AI models, DRL optimization, dynamic network slicing management, and hierarchical coordination control. Simulations results indicate significant improvements in delay, jitter, PDR, resource utilization, etc.关键词：Walker constellation;QoS;AI prediction;dynamic network slicing;hierarchical coordinated control34|32|0更新时间：2026-01-09
- 摘要：Considering the extremely low signal-to-noise ratio (SNR) issue in satellite internet of things (IoT) communications, an efficient coded LoRa transmission scheme based on channel capacity is proposed. First, the corresponding coded LoRa transmission system model is presented. Next, the hard/soft-decision values for non-coherent demodulation of coded LoRa signals are derived. Then, the channel capacity and achievable code rate of the coded LoRa system based on non-coherent demodulation are analyzed, resulting to the relationship between the bit SNR and ideal channel capacity, as well as approximate channel capacity. Finally, the achievable code rates of the coded LoRa system under different spreading factors is demonstrated by simulation, followed by the performance of the coded LoRa system based on ideal metric and approximate metric under different code rates (including the optimal achievable code rate). Taking Turbo and Hamming codes as examples, the Turbo-LoRa transmission scheme exhibits significant performance advantages over the traditional Hamming-LoRa under the same conditions. The Turbo-LoRa with low code-rates based on ideal metric has a performance gain of about 1dB compared to the same Turbo-LoRa based on approximate metric, while the complexity of the former is much higher than that of the latter. These results have certain guiding significance for the reliable transmission of future satellite IoT.关键词：LoRa technique;non-coherent demodulation;channel capacity;satellite IoT;6G communication66|37|0更新时间：2026-01-09
- 摘要：As a supplement to terrestrial mobile communication networks, low earth orbit (LEO) satellite Internet has become an important development direction in the global aerospace and communications fields. Foreign LEO constellations represented by Starlink and OneWeb have begun to provide commercial services. Faced with important opportunities and challenges in building a space-integrated-ground information network, the signal waveform that can be compatible with both terrestrial mobile communication and satellite communication is one of the key technologies for achieving satellite-terrestrial integrated communication. Aiming at the signal waveform of the OneWeb LEO constellation, its frame structure and key details are studied and analyzed. Based on this, the key design parameters and core design ideas of the OneWeb signal waveform are analyzed. Furthermore, a comparative analysis is conducted between the OneWeb signal waveform and typical signal waveforms such as 4G/5G and DVB. The analysis provides certain reference and application value for the signal waveform design and engineering implementation of China's satellite internet constellations.关键词：OneWeb;LEO constellation;satellite internet;signal waveform;satellite-terrestrial integrated170|273|0更新时间：2026-01-09
Studies
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