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TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

US & West · 26 Sept

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.

Relevant to DT products

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Original headline: TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

Read the original: arXiv API — полнотекстовый поиск "digital twin"

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TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

Relevant to DT products

Related

Schneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twin

Large Language Models Meet Bayesian Optimization: Towards Self-evolving Wireless Digital Twins

Digital Twins of Networked Dynamical Systems: Machine Learning Prediction of Synchronization Transitions in Coupled Chaotic Oscillators