论文标题
均匀与非均匀的粗量量化中的相互信息，使LDPC解码最大化
Uniform vs. Non-Uniform Coarse Quantization in Mutual Information Maximizing LDPC Decoding
论文作者
论文摘要
最近，已经引入了低分辨率的LDPC解码器，该解码器执行最大化信号处理的相互信息。但是，变量和检查节点中的最佳量化需要昂贵的非均匀操作。取而代之的是，我们建议使用简单的硬件结构使用统一的量化，从而将单个节点操作的复杂性大约降低到一半，并大大缩短解码延迟。我们的分析表明，由于限制到统一量化而导致的保留的相互信息的丢失非常小。此外，具有常规LDPC代码的错误率模拟证实，与不均匀的替代方案相比，均匀量化的解码器仅在0.01 dB之内导致较小的性能降解。由于降低了复杂性，尤其是提出的3位解码器是替代4位常规解码器的有前途的候选人。
Recently, low-resolution LDPC decoders have been introduced that perform mutual information maximizing signal processing. However, the optimal quantization in variable and check nodes requires expensive non-uniform operations. Instead, we propose to use uniform quantization with a simple hardware structure, which reduces the complexity of individual node operations approximately by half and shortens the decoding delay significantly. Our analysis shows that the loss of preserved mutual information resulting from restriction to uniform quantization is very small. Furthermore, the error rate simulations with regular LDPC codes confirm that the uniformly quantized decoders cause only minor performance degradation within 0.01 dB compared to the non-uniform alternatives. Due to the complexity reduction, especially the proposed 3-bit decoder is a promising candidate to replace 4-bit conventional decoders.
