The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Analysis of Inter-Satellite Link Paths for LEO Mega-Constellation Networks
Abstract
Mega-constellation networks (MCNs) based on low earth orbit (LEO) satellites have become increasingly important with many projects in the design or implementation phase. For those MCN systems with inter-satellite links (ISLs), the large number of satellites increases the routing complexity and the required hop-count of ISL paths. This paper aims to provide insights into the topology and routing design in MCNs through the analysis of ISL paths. We propose a theoretical model to explicitly estimate the ISL hop-count between ground users in MCNs with inclined orbits. The spatial distribution properties of hop-count are derived based on the proposed method. Based on an exemplary constellation, that is Starlink, the global distribution patterns of hop-count and the path difference caused by different access satellites are illustrated for the first time. In Starlink, the difference of the paths from different starting satellites can be up to 45 hops. The numerical results show that optimizing the constellation phasing factor can effectively reduce the average hop-count, for both the whole network and specific regional users.
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Integrating LEO satellite constellations with traditional MEO-based GNSS has emerged as a promising enhancement strategy.
“integrating Low Earth Orbit (LEO) satellite constellations with traditional Medium Earth Orbit (MEO)-based GNSS has emerged as a promising enhancement strategy7–9”
From The optimization of low Earth orbit satellite constellation visibility with genetic algorithm for improved navigation potential (2025) · cites this paper as [8]
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Cites
Hybrid constellation design using a genetic algorithm for a LEO-based navigation augmentation system
Ma, F., Zhang, X., Li, X., Cheng, J., Guo, F., Hu, J., & Pan, L. (2020) · GPS Solutions · doi:10.1007/s10291-020-00977-0 · Cited by 82
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Sorted by citations
Towards Multi-Satellite Collaborative Computing via Task Scheduling Based on Genetic Algorithm
Fei, H., Zhang, X., Long, J., Liu, L., & Wang, Y. (2023) · Aerospace · doi:10.3390/aerospace10020095 · Cited by 17
Qin, C., Gao, Y., & Wang, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-16815-7 · Cited by 9
Metadata
- Authors
- Chen, Q., Giambene, G., Yang, L., Fan, C., & Chen, X.
- Affiliations
- National University of Defense Technology (CN)
- University of Siena (IT)
- PLA Academy of Military Science (CN)
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2021-03
- Volume
- 70
- Issue
- 3
- Pages
- 2743-2755
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W3128807435
- Cited by
- 335
- References
- 1
- Citations by year
- 2026: 61 · 2025: 102 · 2024: 81 · 2023: 51 · 2022: 35 · 2021: 5
- FWCI
- 22.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Vehicular Technology (publishedVersion)
- Use Siena air (University of Siena) (submittedVersion)
- Funders
- National Key Research and Development Program of China Stem Cell and Translational Research (2016YFB0502402)
- National Natural Science Foundation of China (11725211, 12002383)
- China Postdoctoral Science Foundation (2019M664019)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Satellite Communication Systems
- Physical Sciences › Engineering › Aerospace Engineering › Space Satellite Systems and Control
- Physical Sciences › Engineering › Aerospace Engineering › Spacecraft Dynamics and Control
- Keywords
- low Earth orbit satellites, inter-satellite links, network topology, satellite routing, inclined orbits, Starlink
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