A quantized message passing decoding algorithm for low-density parity-check codes is presented. The algorithm relies on the min approximation at the check nodes, and on modelling the variable node inbound messages as observations of an extrinsic discrete memoryless channel. The performance of the algorithm is analyzed and compared to quantized min-sum decoding by means of density evolution, showing remarkable gains and almost closing the gap with the performance of the sum-product algorithm. A stability analysis is derived, which highlights the role played by degree-3 variable nodes in the stability condition. Finite-length simulation results confirm large gains predicted by the asymptotic analysis.

翻译：提供了低密度对等检查代码的量化信息通过解码算法。 算法依赖于检查节点的最小近似值, 以及将可变节点输入信息建模作为外部离散无记忆信道的观测结果。 对算法的性能进行了分析, 并将之与通过密度演进方式量化的微和解码法的性能进行比较, 显示了显著的增益, 并几乎缩小了与总产品算法性能的差距。 得出了稳定性分析, 以突出第3级变量节点在稳定性状况中的作用。 精度模拟结果证实了无损分析所预测的巨大收益 。