Distributed satellite information networks: Architecture, enabling technologies, and trends

TL;DR

This paper surveys the architecture, enabling technologies, and trends of distributed satellite information networks (DSIN), highlighting their potential to support resilient, flexible, and scalable space information services amidst current challenges.

Contribution

It provides a comprehensive overview of DSIN architectures, identifies key enabling technologies, and discusses future research directions for next-generation satellite networks.

Findings

DSIN architectures enable flexible communication, computing, and control.

Key technologies include channel modeling, distributed MIMO, and cross-layer optimization.

Emerging research directions aim to realize resilient and efficient DSIN.

Abstract

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.