面向异构信息传输的分布式低轨小卫星星群对地协同传输机制研究

Distributed LEO small satellite cluster is naturally suitable for collaborative tasks such as weather forecast, environment monitoring, target surveillance and communications benefit from its low earth orbit. However, with the coexistence of communication and earth observation data in the same satellite cluster, the measurement metrics of transmission performance various with different data, raising new challenges to the design of collaborative mechanism for satellite cluster. Moreover, small LEO satellite cluster undergoes severe spectrum shortage, highly dynamic and time-varying topology, short contact time with users on earth, function limitation of the small satellite and so on, making it more difficult to enhance the transmission ability of satellite cluster through collaboration. We first quantify the heterogeneous transmission need of heterogeneous information and establish the optimization target by fully taking into consideration of the above constraints. In this way, we respectively design the collaborative mechanism for different data accordingly. For the transmission of internet data, we investigate the problem of multiuser partitioning using the round-robin service mechanism to guarantee user fairness, and then propose a user-centric clustering scheme and improve the spectral efficiency of satellite cluster. As for the transmission of payload data, we adopt the dynamic graph model to jointly optimize the inter satellite relaying that allows satellites to offload data within the satellite cluster via inter-satellite links and the scheduling between the satellite and the earth station, such that the throughput of data downloading at the earth station. The expected results of this project will promote the application of distributed small LEO satellite cluster in future global internet and space information networks. Furthermore, it will provide both theoretical and technical support to improve the transmission ability and resource utilization in small LEO satellite cluster.

分布式低轨小卫星星群天然的轨道优势使其能协同完成对地观察、测量、导航、通信等多种空间任务，但是星群内通信数据和对地观测数据共存，引发了信息传输性能指标的异构问题，如何设计协作传输机制来提高星群对异构性能要求的适应性，成为新的挑战性课题。本项目充分考虑星群拓扑高动态时变、对地过境时间短、单星功能受限、可用频谱资源紧缺等约束，对通信数据和对地观测数据各异的传输需求进行量化分析并设计协作架构。然后，分别从星群干扰管理和动态资源调度与优化角度出发，提出用户分时调度及以用户为中心的多星协作预编码策略，满足通信用户QoE需求的同时提高频谱效率；基于动态图模型联合优化星间数据中继与星地调度，实现星群观测数据高效能对地回传。本项目的研究将促进分布式低轨小卫星星群在未来全球互联网、天地一体化信息网络中的广泛应用，并为提高分布式小卫星系统传输能力和资源利用率提供理论和技术支撑。

分布式低轨小卫星星群天然的轨道优势使其能协同完成对地观察、测量、导航、通信等多种空间任务，但是星群内通信数据和对地观测数据共存，引发了信息传输性能指标的异构问题，如何设计协作传输机制来提高星群对异构性能要求的适应性，面临极大挑战。本项目考虑星地信道特征、单星功能受限、可用频谱资源紧缺等约束，.首先提出了适用于多LEO卫星的多星协同传输架构。然后，从星群干扰管理和动态资源调度与优化角度出发，提出以用户为中心的多星协作预编码策略，满足通信用户服务质量需求的同时提高频谱效率；结合凸优化理论和机器学习方法，设计轻量级多波束卫星星上快速波束赋形算法。.主要工作总结为：1）提出基于联合预编码的多LEO卫星多网关星地融合架构，并研究了用户速率最大的波束赋形问题。在卫星单天线功率约束和参与协作LEO卫星簇大小约束下，提出基于连续凸近似算法的多星联合波束赋形算法，有效降低邻星干扰。2）考虑更适应卫星低信噪比信道特征的多播传输和星上运算能力限制等因素，针对单星多播传输场景，设计基于用户子集合选择的轻量级波束赋形算法。3）进一步降低多播波束赋形算法计算复杂度，利用机器学习行列式点过程和信道矩阵分解，设计快速多播波束赋形算法，实现算法性能和复杂度折衷。.本研究相关工作旨在促进分布式低轨小卫星星群在未来全球互联网、天地一体化信息网络中的广泛应用，并为提高分布式小卫星系统传输能力和资源利用率提供理论和技术支撑。

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