The work shows that 3D point clouds with semantic labels enable more precise location-tagged channel predictions than 2D visuals in measured real-world settings and releases a paired dataset.
RME-GAN: A learning framework for radio map estimation based on conditional generative adversarial network
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Towards Precise Channel Knowledge Map: Exploiting Environmental Information from 2D Visuals to 3D Point Clouds
The work shows that 3D point clouds with semantic labels enable more precise location-tagged channel predictions than 2D visuals in measured real-world settings and releases a paired dataset.