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# SimComm: Wireless Network Simulator
[](https://github.com/muhd-umer/simcomm/actions?query=workflow:"build")
[](https://github.com/muhd-umer/simcomm/releases/)
[](#license)
[](https://simcomm.readthedocs.io/)
[](https://numpy.org/)
[](https://scipy.org/)
[](https://numba.pydata.org/)
[](https://pytorch.org/)
**SimComm** is a Python library for simulating wireless communication systems. It uses **NumPy** and **SciPy** for numerical computation, and **Numba** for just-in-time (JIT) compilation. It provides a number of features for simulating wireless communication systems:
- **B5G Features**: Supports a variety of B5G specific features, such as STAR-RIS, and NOMA.
- **Channel Models**: Provides the AWGN, Rayleigh, and Rician fading models.
- **Signal Modulation**: Supports a variety of modulation schemes, such as BPSK, QPSK, and QAM.
- **Performance Metrics**: Can calculate a variety of performance metrics, such as the sum rate, and outage probability.
## To-Do
- [ ] Update documentation
- [ ] Add network optimization support
- [ ] Add Reinforcement Learning (RL) support
## Installation
You can install the latest version of the package using pip:
```shell
pip install simcomm
```
*Note: It is recommended to create a new virtual environment so that updates/downgrades of packages do not break other projects.*
Or you can clone the repository along with research code and perform an editable installation:
```shell
git clone https://github.com/muhd-umer/simcomm.git
pip install -e .
```
**Advanced Dependencies**
*Experimental - These libraries are not currently in-use, but will gradually be an integral part of the library.*
- Install PyTorch (Stable):
```shell
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
```
- Install Ray for Reinforcement Learning:
```shell
pip install ray[default]
pip install ray[air]
pip install ray[tune]
pip install ray[rllib]
pip install ray[serve]
```
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