GLIP: Electromagnetic Field Exposure Map Completion by Deep Generative Networks

arXiv:2405.03384v1 Announce Type: new
Abstract: In Spectrum cartography (SC), the generation of exposure maps for radio frequency electromagnetic fields (RF-EMF) spans dimensions of frequency, space, and time, which relies on a sparse collection of sensor data, posing a challenging ill-posed inverse problem. Cartography methods based on models integrate designed priors, such as sparsity and low-rank structures, to refine the solution of this inverse problem. In our previous work, EMF exposure map reconstruction was achieved by Generative Adversarial Networks (GANs) where …

abstract arxiv collection cs.lg data deep generative networks dimensions fields generative map maps networks radio sensor space spectrum type