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Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments
Over the last years, several works have explored the application of deep learning algorithms to determine the large-scale signal fading (also referred to as ``path loss'') between transmitter and receiver pairs in urban communication networks.
The First Pathloss Radio Map Prediction Challenge
To foster research and facilitate fair comparisons among recently proposed pathloss radio map prediction methods, we have launched the ICASSP 2023 First Pathloss Radio Map Prediction Challenge.
On the Effective Usage of Priors in RSS-based Localization
In this paper, we study the localization problem in dense urban settings.
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