MATLAB Implementation of LDPC Encoding and Decoding

This article presents a MATLAB-based implementation of LDPC encoding and decoding algorithms. The program comprises multiple functional modules including encoding, decoding, and modulation components. LDPC codes represent a crucial error-correction technique that efficiently detects and corrects errors during data transmission. The implementation employs advanced algorithms such as iterative message-passing decoding (e.g., sum-product or min-sum algorithms) and efficient encoding techniques using sparse matrix operations. The encoding module utilizes parity-check matrix generation methods, while the decoding module implements probability propagation algorithms with configurable iteration counts. The system also incorporates flexible modulation schemes (including BPSK, QPSK, and higher-order modulations) to adapt to various channel conditions. Key MATLAB functions involved include sparse matrix manipulation for parity-check matrices, logarithmic likelihood ratio (LLR) calculation, and constellation mapping for modulation. This comprehensive implementation demonstrates practical approaches to channel coding optimization and provides insights into LDPC code performance under different signal-to-noise ratios and modulation schemes.