I took the lessons learned here and am building a new tool with physical layer models (channel, interference, ...) and a reinforcement learning environment, it will be public soon. I am keeping this page up as it has the code for the paper below.

Holistic wireless network deployment simulator with regard to the general interconnectedness of all things. Or a 3D Aerial Wireless Networks deployment simulator with continous space and reasonably fast analytical raytracing. If this is interesting to you, please consider reading the following article, which is why this repo exists:

@inproceedings{uluturk2019efficient,
  title={Efficient 3D Placement of Access Points in an Aerial Wireless Network},
  author={Uluturk, Ismail and Uysal, Ismail and Chen, Kwang-Cheng},
  booktitle={2019 16th IEEE Annual Consumer Communications \& Networking Conference (CCNC)},
  pages={1--7},
  year={2019},
  organization={IEEE}
}