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.

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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.

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Requirements

• Python 3.8+
• PyTorch 2.0+
• NumPy 1.23+

Install the required packages using:

pip install torch numpy