构建跨卫星系统的分布式信息网络,打通通信导航遥感数据孤岛
Distributed satellite information networks: Architecture, enabling technologies, and trends

- 通过集群卫星架构实现通信、计算与控制的分布式协同
- 提出多维度技术组合应对异构网络与资源稀缺挑战
- 适合关注未来空天信息网络架构的研究者与工程师
为实现无处不在的连接与无线智能,基于超密集星座的星地融合互联网正逐步成型。然而,现有卫星系统受制于体制壁垒与有限、不可再生的异构网络资源,难以满足下一代智能应用的需求。在此背景下,分布式卫星信息网络(DSIN)应运而生,以协同集群卫星系统为例,弥合通信、导航、遥感等各类卫星系统间的信息鸿沟,构建统一开放的信息网络范式,支撑韧性空间信息服务。本文深入探讨了DSIN的创新网络架构,包括分布式再生卫星网络、分布式卫星计算网络以及可重构卫星编队飞行,以实现灵活可扩展的通信、计算与控制。面对网络异构性、信道动态不确定、资源稀疏及去中心化协作等挑战,识别出一系列使能技术:信道建模与估计、云原生分布式MIMO协作、免授权大规模接入、网络路由,并合理组合多种多样性技术。为进一步提升整体资源效率,发展了跨层优化技术,以满足上层确定性、自适应和安全的信息服务需求。最后,展望了迈向DSIN愿景的新兴研究方向与新机遇。
原文摘要 · Abstract (English)
Driven by the vision of ubiquitous connectivity and wireless intelligence, the evolution of ultra-dense constellation-based satellite-integrated Internet is underway, now taking preliminary shape. Nevertheless, the entrenched institutional silos and limited, nonrenewable heterogeneous network resources leave current satellite systems struggling to accommodate the escalating demands of next-generation intelligent applications. In this context, the distributed satellite information networks (DSIN), exemplified by the cohesive clustered satellites system, have emerged as an innovative architecture, bridging information gaps across diverse satellite systems, such as communication, navigation, and remote sensing, and establishing a unified, open information network paradigm to support resilient space information services. This survey first provides a profound discussion about innovative network architectures of DSIN, encompassing distributed regenerative satellite network architecture, distributed satellite computing network architecture, and reconfigurable satellite formation flying, to enable flexible and scalable communication, computing and control. The DSIN faces challenges from network heterogeneity, unpredictable channel dynamics, sparse resources, and decentralized collaboration frameworks. To address these issues, a series of enabling technologies is identified, including channel modeling and estimation, cloud-native distributed MIMO cooperation, grant-free massive access, network routing, and the proper combination of all these diversity techniques. Furthermore, to heighten the overall resource efficiency, the cross-layer optimization techniques are further developed to meet upper-layer deterministic, adaptive and secure information services requirements. In addition, emerging research directions and new opportunities are highlighted on the way to achieving the DSIN vision.
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