Turbo Code Decoding Program with Log-MAP Algorithm Implementation

In Turbo code decoding, the Log-MAP algorithm serves as an effective decoding technique. The core concept of this algorithm involves using iterative calculations to approximate the maximum likelihood solution for encoded codewords, thereby enabling successful decoding of Turbo-encoded data. Specifically, the algorithm employs logarithmic likelihood ratios (LLRs) to compute decision metrics, which achieves high computational efficiency in software implementations. This implementation typically involves forward and backward recursion calculations through the trellis structure, with soft-input soft-output (SISO) components exchanging extrinsic information between decoders. The logarithmic transformation allows replacing complex multiplication operations with simpler additions, significantly reducing computational complexity while maintaining numerical stability. Therefore, we can integrate the Log-MAP algorithm as a reusable subroutine to achieve high-performance decoding of Turbo codes, with parameters configurable for different constraint lengths and iteration counts.