Convolutional Code Simulation and Performance Analysis

In this document, we comprehensively explore convolutional code implementations and related research papers, providing complete program code and Bit Error Rate (BER) performance graphs. The project includes detailed convolutional code simulation and performance analysis using MATLAB, where we implement encoding/decoding algorithms to systematically evaluate the advantages, disadvantages, and performance characteristics of convolutional codes. The MATLAB implementation typically involves key functions such as: 4. poly2trellis() for creating trellis structure from generator polynomials 2. convenc() for convolutional encoding 3. vitdec() for Viterbi decoding algorithm implementation 4. biterr() for calculating bit error rates Through these detailed analyses and code implementations, we gain deeper understanding of convolutional code working principles and practical applications, establishing a solid foundation and guidance for further research and implementation of convolutional codes in communication systems. The simulation includes performance comparisons under different channel conditions and code parameters, providing insights into optimal configuration selection for various communication scenarios.