https://github.com/nooridan/blahutarimoto

pyTorch implementation of blahut-arimoto alogirthm to compute the channel capacity of a peak power constrained channel
https://github.com/nooridan/blahutarimoto

additive-gaussian-processes channel-cpacity gpu-computing information-theory pytorch

Last synced: about 19 hours ago
JSON representation

pyTorch implementation of blahut-arimoto alogirthm to compute the channel capacity of a peak power constrained channel

• Host: GitHub
• URL: https://github.com/nooridan/blahutarimoto
• Owner: NooriDan
• Created: 2024-12-01T18:03:30.000Z (21 days ago)
• Default Branch: main
• Last Pushed: 2024-12-16T03:48:02.000Z (6 days ago)
• Last Synced: 2024-12-16T04:29:39.065Z (6 days ago)
• Topics: additive-gaussian-processes, channel-cpacity, gpu-computing, information-theory, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 86 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Blahut-Arimoto Algorithm for Channel Capacity Computation (PyTorch Implementation)

## Overview

This project provides a **PyTorch implementation** of the **Blahut-Arimoto algorithm** to compute the channel capacity of a peak power-constrained channel. The Blahut-Arimoto algorithm is a well-established numerical method for evaluating channel capacity, and this implementation leverages PyTorch's efficient tensor operations for performance and scalability.

---

## Features

- **Peak Power Constrained Channel**: Compute channel capacity with constraints on the input power.  

- **PyTorch Integration**: Utilize PyTorch's GPU-accelerated tensor operations for efficient computation.  

- **Customizability**: Easily adapt the code to various channel models and constraints.  

---

## Requirements

- Python 3.8+

- PyTorch 2.0+

- NumPy 1.23+

Install the required packages using:

```bash

pip install torch numpy