Clustering Strategies in Satellite-Aided Communications

Tam Ninh Thi-Thanh; Nguyen Minh Quan; Do Son Tung; Trinh Van Chien; Hung Tran

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arXiv · 2509.13701

Clustering Strategies in Satellite-Aided Communications

Tam Ninh Thi-Thanh·Nguyen Minh Quan·Do Son Tung·Trinh Van Chien·Hung Tran

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Abstract

With the rapid advancement of next-generation satellite networks, addressing clustering tasks, user grouping, and efficient link management has become increasingly critical to optimize network performance and reduce interference. In this paper, we provide a comprehensive overview of modern clustering approaches based on machine learning and heuristic algorithms. The experimental results indicate that improved machine learning techniques and graph theory-based methods deliver significantly better performance and scalability than conventional clustering methods, such as the pure clustering algorithm examined in previous research. These advantages are especially evident in large-scale satellite network scenarios. Furthermore, the paper outlines potential research directions and discusses integrated, multi-dimensional solutions to enhance adaptability and efficiency in future satellite communication.

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Tam Ninh Thi-Thanh, Nguyen Minh Quan, Do Son Tung, Trinh Van Chien, Hung Tran. 2025-09-17. Clustering Strategies in Satellite-Aided Communications. https://arxiv.org/abs/2509.13701

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