Communication Simulation for Learning Information Theory

Abstract

This paper proposes an educational system for understanding information theory. This system allows learners to experience the process of sending messages from the transmitter to the receiver through a noisy communication channel. The transmitter compresses the message string using Huffman coding and adds redundancy using Hamming coding. The result is saved as a text file simulating a noisy communication channel by randomly flipping 0s and 1s. The receiver opens this text file, performs error correction using Hamming decoding, and decompresses the message using Huffman decoding to restore the original string. By rewriting the Python program that implements these processes, learners can practically learn the basic concepts of information theory.