Performance Comparison of Different LDPC Decoding Algorithms

In this paper, we conduct a comparative study of different decoding algorithms for LDPC codes. The algorithms under evaluation include, but are not limited to, iterative decoding algorithms and Min-Sum decoding algorithms. Our analysis focuses on LDPC codes with a code length of 512 and a code rate of 1/2. The iterative decoding approach typically implements message passing between variable and check nodes using the belief propagation (BP) algorithm, where log-likelihood ratios (LLRs) are updated through multiple iterations. The Min-Sum algorithm, as a simplified version, approximates the computationally intensive BP by using minimum operations and correction factors to reduce complexity while maintaining acceptable performance. Through performance comparison of these decoding algorithms, we gain deeper insights into LDPC code behavior under different scenarios, providing valuable reference data for practical applications in communication systems. The comparison metrics include bit error rate (BER) performance, convergence speed, and computational complexity, which are crucial for algorithm selection in real-world implementations.