QC-LDPC Encoding and Decoding Algorithms

In this article, we explore QC-LDPC (Quasi-Cyclic Low-Density Parity-Check) encoding and decoding algorithms and demonstrate how they facilitate SER simulations for QC-LDPC codes. Encoding and decoding algorithms are error-correction techniques designed to efficiently detect and correct transmission errors. By implementing QC-LDPC encoding—typically through cyclic shift operations on base matrices to generate structured parity-check matrices—we enhance the reliability and performance of communication systems. During simulation, different transmission conditions and noise levels can be modeled, often using BPSK modulation over AWGN channels, to evaluate QC-LDPC performance. The decoding process commonly employs iterative algorithms like the Sum-Product or Min-Sum algorithm, updating belief propagation between variable and check nodes to minimize errors. These simulations help deepen our understanding of QC-LDPC code design and optimization. We hope this article provides detailed insights into QC-LDPC algorithms and inspires further interest in this field.