论文标题
卷积极性内核
Convolutional Polar Kernels
论文作者
论文摘要
一个偏振核的家族与多项式复杂性算法一起呈现，用于计算缩放指数。提出的卷积极性内核基于卷积极性代码，也称为B-MERA代码。对于这些内核，提出了多项式复杂性算法，以找到计算缩放指数所需的不可恢复的擦除模式的重量谱。结果，我们获得了最高1024的卷积极性内核的缩放指数和极化速率。
A family of polarizing kernels is presented together with polynomial-complexity algorithm for computing scaling exponent. The proposed convolutional polar kernels are based on convolutional polar codes, also known as b-MERA codes. For these kernels, a polynomial-complexity algorithm is proposed to find weight spectrum of unrecoverable erasure patterns, needed for computing scaling exponent. As a result, we obtain scaling exponent and polarization rate for convolutional polar kernels of size up to 1024.
