Implementation of Convolutional Coding with BPSK Modulation, Viterbi Decoding, and Comparison of Soft/Hard Decision vs. Uncoded BPSK Bit Error Rate

In this article, we focus on implementing convolutional coding with BPSK modulation and Viterbi decoding, including both soft and hard decision approaches. To better understand these concepts, we conduct comparative analysis with uncoded BPSK bit error rate performance, providing detailed explanations for each implementation step. Throughout this process, we explore different implementation methodologies and their impact on system performance and accuracy. We also examine the latest technological developments and trends to help readers stay current with advancements in this field. The implementation typically involves generating convolutional codes using polynomial generators, modulating with BPSK through constellation mapping, and decoding using the Viterbi algorithm which employs trellis-based path metric calculations. For soft decision decoding, we implement log-likelihood ratio (LLR) calculations using Euclidean distance metrics, while hard decision uses simple binary thresholding. Through this article, readers will gain deeper understanding of convolutional coding with BPSK modulation and Viterbi decoding, along with comprehensive comparison techniques for evaluating uncoded BPSK bit error rates. We hope this article provides valuable insights into the knowledge and techniques in this domain.