English(EN) TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

TRACE框架使用射频测量实现无线数字孪生的自校准

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员开发了TRACE，一个使用射频测量来自校准无线数字孪生的新框架。该系统解决了现有数字孪生中的不准确性，这些不准确性通常源于不完美的3D环境模型。TRACE通过射线追踪孪生、反投影测量和模拟的射频数据以及提取建筑物周围的局部区域来对齐物理世界和数字孪生之间的残差误差。然后，一个多视图校正器融合证据，预测建筑物参数的校正，从而显著提高位置和方向的准确性。 AI

影响提高了无线数字孪生的准确性，可能增强网络规划和优化。

排序理由该集群包含一篇详细介绍新框架及其在合成和真实世界数据上性能的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Saad Masrur, Saeed R. Khosravirad, Ismail Guvenc · 2026-10-01 04:00

TRACE：从ISAC测量中学习无线数字孪生自校准

arXiv:2609.32923v2 Announce Type: replace Abstract: Wireless digital twins (DTs) rely on 3D environment models to predict radio propagation and support wireless-network decisions, yet these models are often initialized from imperfect 3D maps. Errors in building position, height, …

本文如何被排名

报道来源 [1]

TRACE：从ISAC测量中学习无线数字孪生自校准

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