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English(EN) QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks

新框架预测无线电地图以实现主动无线自适应

研究人员开发了QuaMoE-DRF,一个用于优化集成接入与回传(ISAC)网络中无线通信的新型框架。该系统通过预测动态无线电地图来主动调整波束成形和数据速率,解决了静态地图和直接传感方法的局限性。QuaMoE-DRF整合了几何、运动和历史无线数据等多种数据源,以预测未来的通信条件,并为基站和用户设备做出明智的决策。 AI

影响 该框架通过实现更智能的资源分配,有望提高无线网络的效率和可靠性。

排序理由 这是一篇详细介绍无线通信新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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新框架预测无线电地图以实现主动无线自适应

报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Zhihan Zeng, Kaihe Wang, Zhongpei Zhang, Chongwen Huang ·

    QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks

    arXiv:2607.00974v1 Announce Type: cross Abstract: Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-assisted beam prediction is also limited because a beam index discards SINR marg…

  2. arXiv cs.CV TIER_1 English(EN) · Chongwen Huang ·

    QuaMoE-DRF:在ISAC网络中通过多模态动态无线电地图预测进行主动波束和速率自适应

    Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-assisted beam prediction is also limited because a beam index discards SINR margins, MCS thresholds, BS alternatives, and communic…