LEO Satellite Access Network (LEO-SAN) Towards 6G: Challenges and Approaches
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Abstract (arXiv)
With the rapid development of satellite communication technologies, the space-based access network has been envisioned as a promising complementary part of the future 6G network. Aside from terrestrial base stations, satellite nodes, especially the low-earth-orbit (LEO) satellites, can also serve as base stations for Internet access, and constitute the LEO-satellite-based access network (LEO-SAN). LEO-SAN is expected to provide seamless massive access and extended coverage with high signal quality. However, its practical implementation still faces significant technical challenges, e.g., high mobility and limited budget for communication payloads of LEO satellite nodes. This paper aims at revealing the main technical issues that have not been fully addressed by the existing LEO-SAN designs, from three aspects namely random access, beam management and Doppler-resistant transmission technologies. More specifically, the critical issues of random access in LEO-SAN are discussed regarding low flexibility, long transmission delay, and inefficient handshakes. Then the beam management for LEO-SAN is investigated in complex propagation environments under the constraints of high mobility and limited payload budget. Furthermore, the influence of Doppler shifts on LEO-SAN is explored. Correspondingly, promising technologies to address these challenges are also discussed, respectively. Finally, the future research directions are envisioned.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Jul 2022.
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Citing papers per year: 2024: 3; 2025: 2.
5 papers.
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- 2024Edge-Cloud Collaborative Satellite Image Analysis for Efficient Man-Made Structure Recognitioncited by 0
- 2025Joint AoI and Handover Optimization in Space-Air-Ground Integrated Networkcited by 0
- 2025Joint AoI and Handover Optimization in Space-Air-Ground Integrated Network16 Sep 2025
- 2025Multi-Functional RIS-Enabled in SAGIN for IoT: A Hybrid Deep Reinforcement Learning Approach with Compressed Twin-Models22 Jul 2025
- 2024Edge-Cloud Collaborative Satellite Image Analysis for Efficient Man-Made Structure Recognition8 Oct 2024
- 2024SATSense: Multi-Satellite Collaborative Framework for Spectrum Sensing24 May 2024
- 2024Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission14 Apr 2024