Implementation of Convolutional Code Encoding and Decoding Using Simulink

In this document, we explore how to implement convolutional code encoding and decoding functions using Simulink, along with bit error rate (BER) analysis. Convolutional coding is a widely used channel coding technique in communication systems that enhances data transmission reliability. Through Simulink, we can efficiently design and implement convolutional code encoding and decoding algorithms using built-in blocks such as the Convolutional Encoder and Viterbi Decoder blocks. The implementation typically involves configuring code parameters like constraint length and generator polynomials for the encoder, while the decoder uses maximum likelihood sequence estimation through the Viterbi algorithm. BER analysis serves as a critical performance evaluation method, allowing us to assess system performance under various channel conditions. We can implement BER analysis using the Error Rate Calculation block and visualize results with scopes or plots. This document provides detailed guidance on utilizing Simulink for implementing convolutional code operations and conducting BER analysis to better understand and evaluate system performance.