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Physics-informed neural networks for pathloss prediction
This paper introduces a physics-informed machine learning approach for pathloss prediction.
Generative Adversarial Networks for Pseudo-Radio-Signal Synthesis
For many wireless communication applications, traffic pattern modeling of radio signals combined with channel effects is much needed.
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