| Name | comyx JSON |
| Version |
0.2.4
JSON |
| download |
| home_page | None |
| Summary | Comyx is an optimized and modular Python library for simulating wireless communication systems. |
| upload_time | 2024-03-24 19:44:26 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
python
communication
simulator
wireless communication
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
|
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# Comyx: Wireless Network Simulator
[](https://github.com/muhd-umer/comyx/actions?query=workflow:"build")
[](https://github.com/muhd-umer/comyx/releases/)
[](#license)
[](https://comyx.readthedocs.io/)
[](https://numpy.org/)
[](https://scipy.org/)
[](https://numba.pydata.org/)
[](https://pytorch.org/)
**Comyx** 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 comyx
```
*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/comyx.git
pip install -e .
```
**Reinforcement Learning (RL) Support**
For RL support, you will need to install the following dependencies:
- Install PyTorch (Stable)
```shell
pip install torch torchvision torchaudio
```
- Install Ray RLlib
```shell
pip install -U ray[default] # core, dashboard, cluster launcher
pip install -U ray[rllib] # tune, rllib
```
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