DRL-LANCP (Link: IEEE TMC) investigates how to improve the generalization of low-altitude radio map prediction by disentangling propagation-related representations, bridging data learning with implicit physical structure.
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RadioGAT (Link: IEEE TWC, code) studies how to perform reliable cross-band radio map prediction when measurement data are sparse and irregularly distributed, by learning wireless spatial correlations in a graph-based manner.
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