MATLAB Implementation of Turbo Code Decoding

This article provides an in-depth exploration of turbo code decoding implementation in MATLAB. Turbo codes are widely used encoding schemes in wireless communications, and their decoding process involves two distinct algorithms: LOGMAP and SOVA. The LOGMAP algorithm is a logarithmic-based decoding approach that performs decoding by calculating log-likelihood ratios (LLR) from hard decisions. In MATLAB implementation, this typically involves using the log-sum-exp trick for stable numerical computation when handling probability values. The SOVA (Soft Output Viterbi Algorithm) is an iterative decoding method that computes likelihood ratios through soft decisions in each iteration, gradually improving decoding accuracy. The MATLAB implementation of SOVA involves maintaining path metrics and soft output values throughout the trellis traversal. This article presents detailed implementation procedures for both algorithms, including key MATLAB functions such as likelihood ratio calculations, iterative processing loops, and termination criteria. We analyze the comparative advantages and disadvantages of each algorithm in terms of computational complexity, error correction performance, and implementation efficiency. The discussion covers practical implementation aspects like handling numerical stability in logarithmic calculations and managing memory requirements for path metrics storage. Furthermore, we examine turbo code applications in modern communication systems and their future development directions, including potential enhancements for 5G and beyond wireless technologies. The content provides comprehensive technical insights suitable for engineers and researchers working on channel coding implementations.