Dissecting and Implementing SOYA Algorithm Variations in Convolutional and Turbo Code Decoding: An Analytical Approach

Turbo coding, a forward error correction code scheme, was introduced by Berrou and Glavieux at the 1993 ICC International Conference. It is widely used in various fields of communication, including mobile communication, image and video transmission, and deep space communication. Notably, it was the first code to approach the Shannon limit. However, the traditional Viterbi algorithm, which calculates the maximum likelihood (ML) sequence of convolutional code for decoding, provides only a hard output judgement, thereby losing information in a cascading system. This paper pivots from the Viterbi algorithm to derive the reliability information within the turbo decoder, which when combined with the Viterbi algorithm, produces a soft output - also known as the Soft Output Viterbi Algorithm (SOVA). This work also touches upon a simplified SOYA. Although this version leads to a slight performance degradation (0.4 dB), it offers the advantage of simplicity, making it an attractive choice for certain applications. The SOYA algorithm builds upon the traditional Viterbi algorithm and enhances it through soft output. This evolution holds substantial importance for 3G communication systems and related fields.