README.md

PL-GAN Models

IEEE | BibTeX

PL-GAN: Path Loss Prediction using Generative Adversarial Networks
Ahmed Marey, Mustafa Bal, Hasan Ates, Bahadir Gunturk

This is a repository for the Path Loss GAN (PL-GAN) project. PL-GAN infers excess path loss of an area from a satellite or height map image.

Running the evaluation code infer.py will generate the path loss images and the statistical comparison between height map input and satellite image input.

The test set can be downloaded from here. Place it in the test folder and run infer.py.

The figure below shows input images and results for some sample regions.

BibTeX

@ARTICLE{9866771,
  author={Marey, Ahmed and Bal, Mustafa and Ates, Hasan F. and Gunturk, Bahadir K.},
  journal={IEEE Access}, 
  title={PL-GAN: Path Loss Prediction Using Generative Adversarial Networks}, 
  year={2022},
  volume={10},
  number={},
  pages={90474-90480},
  doi={10.1109/ACCESS.2022.3201643}}