HIGHLIGHTS
- What: The authors present an overview of the proposed model, with emphasis on multi-transmitter cases. The aim of the simple geometries is to help the model "learn" basic wave propagation mechanisms, such as edge diffraction, reflection from and transmission through one or more walls. To investigate the accuracy of the trained U-Net on multitransmitter cases, the authors compare its RSS predictions for Nt=2, 3, and 4 concurrently operating transmitters, against the corresponding RT-based RSS values. The authors compare the optimization accuracy between the two cases.
- Who: LICENSE and collaborators from the . . .
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