Shaping LDLC lattices using convolutional code lattices
Shaping LDLC lattices using convolutional code lattices
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使用卷积码晶格塑造 LDLC 晶格
DOI：
10.1109/lcomm.2017.2647922
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
F. Zhou and B. M. Kurkoski
中科院分区：
文献类型：
--
作者：
M. Hori;Y. Ono;F. Zhou and B. M. Kurkoski
在这封信中，我们展示了如何构建低密度格码（LDLC）格使用卷积码格形。首先，我们给出了一种求卷积码格生成矩阵的显式方法。通过计算归一化二阶矩，得到了基于1/2码率卷积码的卷积码格在短块长度下的成形增益，当维数n = 200时，成形增益高达1.24dB，并构造了嵌套LDLC格。我们设计的LDLC格满足必要的条件，形成嵌套格码，并给出了一个具体的例子。对于n = 36维点阵，基于LDLC点阵的点阵码，使用卷积码点阵成形，具有超过超立方体成形的0.87 dB的成形增益。
In this letter, we show how to construct low-density lattice code (LDLC) lattices shaped using convolutional code lattices. First, we give an explicit method to find the generator matrices of convolutional code lattices. The shaping gain of convolutional code lattices based on rate 1/2 convolutional codes for short block length is found by evaluating the normalized second moment; a shaping gain as high as 1.24 dB for dimension n = 200 was found. Then, nested LDLC lattices are constructed. We design LDLC lattices that satisfy conditions necessary for forming nested lattice codes, and give a specific example. For an n = 36 dimensional lattice, a lattice code based on LDLC lattices, shaped using convolutional code lattices, has a shaping gain of 0.87 dB, over hypercube shaping.