论文标题
匹配的低密度平价检查代码的量化量化的最小解码
Matched Quantized Min-Sum Decoding of Low-Density Parity-Check Codes
论文作者
论文摘要
提出了一个量化的消息传递解码算法的低密度奇偶校验检查代码。该算法依赖于检查节点处的最小近似值，以及对可变节点入站消息进行建模作为外部离散无内存通道的观察。分析算法的性能并通过密度演化与量化的微小和解码进行比较，并几乎通过Sum-rapoduct算法的性能缩小了间隙。得出了稳定性分析，该分析突出了稳定性条件下的度数-3 $可变节点的作用。有限长度的仿真结果证实了渐近分析预测的大幅收益。
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, and almost closes 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.
