基于最小和的高效LDPC译码算法

Efficient LDPC Decoding Algorithm Based on Min-sum

针对低密度奇偶校验(LDPC)译码算法性能低的问题,提出一种基于最小和的高效译码算法。该算法从概率的角度分析消息的传递过程中校验节点的更新过程,得到近似的最小和算法等式,并采用动态归一化因子提高译码性能。仿真实验表明,与BP译码算法相比,该译码算法在损失极少译码性能的情况下,不仅减少迭代过程中的计算量,而且提高了译码效率。

To improve the decoding performance of Low Density Parity Check（LDPC） code, an efficient decoding algorithm based on min-sum algorithm is proposed. The proposed algorithm analyzes the check node update equation and at the view of probability to form an approximation min-sum equation. It adopts a dynamic normalization factor to improve the decoding performance. Detailed simulation results and comparisons with Belief Propagation（BP） algorithm show that, with little decoding performance loss, the proposed algorithm not only decreases computational load, but also improves decoding efficiency.