English(EN) Multimodal Spatiotemporal-Frequency Fusion with Peak Enhancement for Cellular Traffic Forecasting

新的 MSPF-Net 框架通过多模态数据改进蜂窝流量预测

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-08 05:17

研究人员开发了 MSPF-Net，一个旨在改进蜂窝网络流量预测的新颖框架。该模型集成了多模态数据，包括时空-频域流量模式、突发行为以及来自新闻流的外部上下文信息。在米兰、特伦托和长期演进 (LTE) 网络数据集上进行的实验表明，这种综合方法显著提高了预测准确性。 AI

影响这项研究可能导致电信领域更高效的网络规划和资源分配。

排序理由该集群包含一篇在 arXiv 上发表的研究论文，详细介绍了一种新的蜂窝流量预测模型。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Qingzhong Li, Yue Hu, Hui Ma, Yajun Zhang, Xinjun Pei, Ming Yan, Fei Xing · 2026-07-09 04:00

多模态时空频融合与峰值增强用于蜂窝流量预测

arXiv:2607.07016v1 Announce Type: cross Abstract: Accurate forecasting of cellular network traffic is essential for network planning, resource allocation, and quality-of-service assurance in modern mobile communication systems. Real-world traffic often exhibits bursty endogenous …
arXiv cs.AI TIER_1 English(EN) · Fei Xing · 2026-07-08 05:17

用于蜂窝流量预测的多模态时空频率融合与峰值增强

Accurate forecasting of cellular network traffic is essential for network planning, resource allocation, and quality-of-service assurance in modern mobile communication systems. Real-world traffic often exhibits bursty endogenous dynamics and disturbances triggered by external ur…