Viterbi Algorithm Implementation for Convolutional Coding in Communication Systems

This project consists of MATLAB m-files designed to study convolutional channel encoding and Viterbi decoding algorithms within simulated communication systems.

In this simulated communication system, we implement convolutional channel encoding and Viterbi decoding algorithms using MATLAB m-files. These algorithms are crucial for enhancing communication system reliability and performance. The convolutional encoding process involves generating parity bits through shift registers and modulo-2 adders, creating redundant bits that enable error correction. The Viterbi decoder employs dynamic programming principles, specifically the maximum likelihood sequence estimation (MLSE) approach, to efficiently recover signals affected by noise and interference by calculating path metrics and tracing back through a trellis diagram. By studying these algorithms, we gain deeper insights into communication system operations and establish practical implementation guidelines. The MATLAB implementation typically includes functions for generating convolutional codes, calculating branch metrics, and executing the Viterbi algorithm's add-compare-select operations.