Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a precoding step before the polar transform. In this scheme, the polar transform (as a mapper) and the successive cancellation process (as a demapper) present a synthetic vector channel to the convolutional transformation. The numerical results in the literature show that this concatenation improves the weight distribution of polar codes which justifies the superior error correction performance of PAC codes relative to polar codes. In this work, we explicitly show why the convolutional precoding reduces the number of minimumweight codewords. Further analysis exhibits where the precoding stage is not effective. Then, we recognize weaknesses of the convolutional precoding which are unequal error protection (UEP) of the information bits due to rate profiling and lack of cross-segmental convolution. Finally, we assess the possibility of improving the precoding stage by proposing some irregular convolutional precodings.
翻译:极化调整后共变( PAC) 代码是特殊的混合代码, 我们使用一到一的共变( PAC) 代码, 作为极变之前的编码步骤。 在这个方法中, 极变( 映射器) 和连续的取消过程( 映射器) 提供了一个合成矢量 渠道, 形成共变。 文献中的数字结果显示, 这种共化改善了极代数的权重分布, 从而证明PAC 代码相对于极代数的超强误差校正性表现是合理的 。 在这项工作中, 我们明确显示, 共变前编码为何会减少最小重量的编码数 。 进一步分析显示预编译阶段无效的地方 。 然后, 我们发现, 共变前编码的弱点是信息位的不平等错误保护( UEP ), 其原因是对率的剖析和缺乏交叉剖析的共变。 最后, 我们通过提出一些非正常的编码来评估改进前编码阶段的可能性 。