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About this paper
Yalin E. Sagduyu, Tugba Erpek, Hossein Jafari
The authors evaluate adaptive receiver selection for estimating a global path-loss offset in a physics-based radio-frequency digital twin. The methods use twin predictions and observed residuals to choose measurement locations. In offline Monte Carlo evaluation on 30 receiver locations, Adaptive Uncertainty-Aware Sampling reduced mean and worst-case offset error by 72.05% and 91.04%, respectively, versus random sampling, averaged across budgets.
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