Scholarlink

<p>Driven by technological advancements and cost reductions, the rapid deployment of low-Earth-orbit (LEO) satellites has led to the emergence of mega-constellations based on inter-satellite links (ISLs). However, the communication performance of satellite networks is easily affected by the time-varying network topology and the link constraints caused by the limited computational resources of satellite nodes. Consequently, the design of ISL allocation algorithms for LEO satellites has become a critical challenge for current mega-constellations. To address this issue, this paper proposes a Non-Dominated Sorting Genetic Algorithm II based on elite selection criteria (ENSGA-II). The satellite network’s ISL allocation problem is modeled as a multi-objective optimization model, where elite selection criteria are employed to preserve solutions with lower delays while optimizing both the average and maximum delays. This approach enhances the overall effectiveness of ISL allocation in satellite networks. Simulation results demonstrate that ENSGA-II exhibits faster link optimization capabilities during the allocation process and significantly improves the communication delay performance of the network topology. Compared to single-point and two-point crossover-based NSGA-II algorithms, the maximum delay was reduced by 3&#xa0;ms and 9&#xa0;ms, and the average delay was reduced by 1&#xa0;ms compared to single-point crossover and was the same as two-point crossover. These findings indicate that ENSGA-II is well suited for ISL allocation in mega-constellations.</p>

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Inter-satellite link allocation in low-earth-orbit mega-constellation networks

  • 期刊论文

  • 发表日期：

    2025年7月16日

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  • Weiwu Ren,
  • Bingsen Wang,
  • Jie Sun,
  • Yu Hong

摘要

Driven by technological advancements and cost reductions, the rapid deployment of low-Earth-orbit (LEO) satellites has led to the emergence of mega-constellations based on inter-satellite links (ISLs). However, the communication performance of satellite networks is easily affected by the time-varying network topology and the link constraints caused by the limited computational resources of satellite nodes. Consequently, the design of ISL allocation algorithms for LEO satellites has become a critical challenge for current mega-constellations. To address this issue, this paper proposes a Non-Dominated Sorting Genetic Algorithm II based on elite selection criteria (ENSGA-II). The satellite network’s ISL allocation problem is modeled as a multi-objective optimization model, where elite selection criteria are employed to preserve solutions with lower delays while optimizing both the average and maximum delays. This approach enhances the overall effectiveness of ISL allocation in satellite networks. Simulation results demonstrate that ENSGA-II exhibits faster link optimization capabilities during the allocation process and significantly improves the communication delay performance of the network topology. Compared to single-point and two-point crossover-based NSGA-II algorithms, the maximum delay was reduced by 3 ms and 9 ms, and the average delay was reduced by 1 ms compared to single-point crossover and was the same as two-point crossover. These findings indicate that ENSGA-II is well suited for ISL allocation in mega-constellations.