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.
- 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.
- Python 3.8+
- PyTorch 2.0+
- NumPy 1.23+
Install the required packages using:
pip install torch numpy