论文标题
与非对称偏差模型的嘈杂密度演化
Noisy Density Evolution With Asymmetric Deviation Models
论文作者
论文摘要
本文认为低密度奇偶校验检查（LDPC）解码器受到实施解码器的电子设备引入的偏差影响的解码器。允许从理论上研究这些LDPC解码器的性能的嘈杂密度演化（DE）只能考虑由于全零代码字假设而考虑的对称偏差模型。提出了一种新的DE方法，该方法承认使用不对称偏差模型，从而扩大了可以分析的错误实现范围。为三个嘈杂的解码器提供了DE方程：信仰传播，Gallager B和量化的Min-sum（MS）。仿真结果证实，所提出的DE可以准确地预测不对称偏差的LDPC解码器的性能。此外，提出了Gallager B和MS解码器的不对称版本，以补偿不对称偏差的影响。然后使用建议的DE优化这些解码器的参数，从而在不对称偏差的情况下提高了更好的集合阈值并改善了有限长度的性能。
This paper considers low-density parity-check (LDPC) decoders affected by deviations introduced by the electronic device on which the decoder is implemented. Noisy density evolution (DE) that allows to theoretically study the performance of these LDPC decoders can only consider symmetric deviation models due to the all-zero codeword assumption. A novel DE method is proposed that admits the use of asymmetric deviation models, thus widening the range of faulty implementations that can be analyzed. DE equations are provided for three noisy decoders: belief propagation, Gallager B, and quantized min-sum (MS). Simulation results confirm that the proposed DE accurately predicts the performance of LDPC decoders with asymmetric deviations. Furthermore, asymmetric versions of the Gallager B and MS decoders are proposed to compensate the effect of asymmetric deviations. The parameters of these decoders are then optimized using the proposed DE, leading to better ensemble thresholds and improved finite-length performance in the presence of asymmetric deviations.
