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English(EN) Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks

Dueling DDQN优化LEO卫星网络切换，吞吐量提升10.3%

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了一种新的自适应多目标切换框架，用于LEO卫星网络，该框架利用了Dueling Double Deep Q-Network (DDQN)。该框架旨在根据不断变化的網絡状况，动态平衡吞吐量、阻塞概率和切换成本。模拟结果表明，这种基于DDQN的方法优于现有方法，吞吐量最高可提高10.3%，同时保持接近零的阻塞率。 AI

影响 这项研究通过优化切换过程，有望实现更高效的卫星通信。

排序理由 这是一篇发表在arXiv上的研究论文，详细介绍了一种用于卫星网络的新框架。

在 arXiv cs.LG 阅读 →

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Dueling DDQN优化LEO卫星网络切换，吞吐量提升10.3%

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报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Po-Heng Chou, Chiapin Wang, Chung-Chi Huang, Kuan-Hao Chen ·

    面向LEO卫星网络的基于Dueling DDQN的自适应多目标切换优化

    arXiv:2605.02416v1 Announce Type: cross Abstract: In this paper, we propose a dueling double deep Q-network (DDQN)-based adaptive multi-objective handover framework for LEO satellite networks. The proposed method enables dynamic trade-off learning among throughput, blocking proba…

  2. arXiv cs.LG TIER_1 English(EN) · Kuan-Hao Chen ·

    基于Dueling DDQN的LEO卫星网络自适应多目标切换优化

    In this paper, we propose a dueling double deep Q-network (DDQN)-based adaptive multi-objective handover framework for LEO satellite networks. The proposed method enables dynamic trade-off learning among throughput, blocking probability, and switching cost under time-varying netw…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    面向LEO卫星网络的基于Dueling DDQN的自适应多目标切换优化

    In this paper, we propose a dueling double deep Q-network (DDQN)-based adaptive multi-objective handover framework for LEO satellite networks. The proposed method enables dynamic trade-off learning among throughput, blocking probability, and switching cost under time-varying netw…

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