SC Decoding Algorithm for Polar Codes with Performance Optimization

The implementation details of the SC decoding algorithm for polar codes can be enhanced with technical specifications. This algorithm supports dynamic configuration of various signal-to-noise ratios and code lengths, with modular architecture allowing seamless transition to SCL (Successive Cancellation List) and CA-SCL (CRC-Aided SCL) decoding variants. The performance-critical decoding core is implemented in C using optimized bit-level operations and recursive probability calculations, while MATLAB handles high-level framework control including parameter initialization, result visualization, and batch simulation management. This hybrid approach leverages C's computational efficiency for intensive calculations and MATLAB's rapid prototyping capabilities, resulting in substantial execution speed improvements compared to pure MATLAB implementations. The system employs logarithmic likelihood ratio (LLR) processing and binary tree traversal algorithms for efficient polarization channel decoding.