Inter-Plane Inter-Satellite Connectivity in Dense LEO Constellations
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Abstract (arXiv)
With numerous ongoing deployments owned by private companies and startups, dense satellite constellations deployed in low Earth orbit (LEO) will play a major role in the near future of wireless communications. In addition, the 3rd Generation Partnership Project (3GPP) has ongoing efforts to integrate satellites into 5G and beyond-5G networks. Nevertheless, numerous challenges must be overcome to fully exploit the connectivity capabilities of satellite constellations. These challenges are mainly a consequence of the low capabilities of individual small satellites, along with their high orbital speeds and small coverage due to the low altitude of deployment. In particular, inter-plane inter-satellite links (ISLs), which connect satellites from different orbital planes, are greatly dynamic and may be considerably affected by the Doppler shift. In this paper, we present a framework and the corresponding algorithms for the dynamic establishment of the inter-plane ISLs in LEO constellations. Our results show that the proposed algorithms increase the sum of rates in the constellation 1) by up to 115% with respect to the state-of-the-art benchmark schemes in an interference-free environment and 2) by up to 71% when compared to random resource allocation in a worst-case scenario for interference.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 May 2020.
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Citing papers per year: 2022: 1; 2023: 3; 2024: 3; 2025: 4; 2026: 1.
12 papers.
- 2022FedHAP: Fast Federated Learning for LEO Constellations Using Collaborative HAPscited by 21
- 2023One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutescited by 7
- 2023Edge Selection and Clustering for Federated Learning in Optical Inter-LEO Satellite Constellationcited by 6
- 2024Continual Deep Reinforcement Learning for Decentralized Satellite Routingcited by 6
- 2023Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloadingcited by 5
- 2024Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approachcited by 4
- 2025Satellite Edge Artificial Intelligence with Large Models: Architectures and Technologiescited by 4
- 2024An open source Multi-Agent Deep Reinforcement Learning Routing Simulator for satellite networkscited by 1
- 2025Brain-Inspired Decentralized Satellite Learning in Space Computing Power Networkscited by 1
- 2025Satellite Federated Fine-Tuning for Foundation Models in Space Computing Power Networkscited by 0
- 2025QoS-Aware Hierarchical Reinforcement Learning for Joint Link Selection and Trajectory Optimization in SAGIN-Supported UAV Mobility Managementcited by 0
- 2026ASTRA: ADMM-Accelerated Topology Reconfiguration for Dynamic Satellite Constellationscited by 0
- 2026ASTRA: ADMM-Accelerated Topology Reconfiguration for Dynamic Satellite Constellations27 Sep 2026
- 2025QoS-Aware Hierarchical Reinforcement Learning for Joint Link Selection and Trajectory Optimization in SAGIN-Supported UAV Mobility Management17 Dec 2025
- 2025Satellite Federated Fine-Tuning for Foundation Models in Space Computing Power Networks14 Apr 2025
- 2025Satellite Edge Artificial Intelligence with Large Models: Architectures and Technologies2 Apr 2025
- 2025Brain-Inspired Decentralized Satellite Learning in Space Computing Power Networks27 Jan 2025
- 2024Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approach17 Oct 2024
- 2024An open source Multi-Agent Deep Reinforcement Learning Routing Simulator for satellite networks8 Jul 2024
- 2024Continual Deep Reinforcement Learning for Decentralized Satellite Routing20 May 2024
- 2023Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading23 Dec 2023
- 2023One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes21 May 2023
- 2023Edge Selection and Clustering for Federated Learning in Optical Inter-LEO Satellite Constellation25 Mar 2023
- 2022FedHAP: Fast Federated Learning for LEO Constellations Using Collaborative HAPs15 May 2022