From a57953823ef7d64266c82435c2434eb14f690526 Mon Sep 17 00:00:00 2001 From: Lukas Eller Date: Mon, 26 Sep 2022 10:15:59 +0200 Subject: [PATCH] Update README.md --- README.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 19899f8..764081a 100644 --- a/README.md +++ b/README.md @@ -8,10 +8,6 @@ Measurements and a 3D City Model."** submitted for publication in IEEE Access. -It includes all the necessary code and data to reproduce the presented network planning scenarios. -Thus, it also includes the models trained on the extensive drive-test campaign. -Interested researchers are invited to also deploy them in other settings. - # Preparing the Repository In order to run the scenarios it is required to download the exemplary environments using the following [link](https://owncloud.tuwien.ac.at/index.php/s/APFp9z2YCPFVb2D). @@ -21,3 +17,5 @@ The obtained `environment/` folder with all contained files has to be stored on The `main` function in `run_scenario.py` runs all scenarios defined in the `scenarios/` folder. Each scenario contains a `config.json` file where parameters such as the height of the base station `h_bs`, the horizontal `phi_sec_h` and vertical `phi_sec_v` sector orientation as well as transmit power and frequence can be adapted. +Per default, the `run_scenario.py` will generate all the scenarios presented in the paper. Note, that the uniform antenna patterns are specified through `phi_sec_h=null`. +We encourage interested readers to adapt the scenario configurations or to apply the trained models to their own use-cases altogether. \ No newline at end of file -- 2.22.0