论文标题
log-ccdm：通过无乘法算术编码进行匹配的分布匹配
Log-CCDM: Distribution Matching via Multiplication-free Arithmetic Coding
论文作者
论文摘要
近年来，人们对算术编码（AC）有了重新关注。这要归功于使用AC进行分配匹配（DM）来控制概率振幅成型中的通道输入分布。 AC固有的两个主要问题：（1）其所需的算术精度随输入长度线性增长，并且（2）需要高精度乘法和划分。在这里，我们通过三个查找表（LUTS）介绍了一个基于无倍数的DM技术，该表解决了上述两个问题。这些LUT用于通过添加和减法来近似高精度的乘法和划分。我们所需的方法的精度显示出与输入长度的对数生长。我们证明，这种近似技术保持了DM的可逆性。在输入长度为1024个符号的情况下，该提议的技术可实现可忽略不计的率损失（$ <0.01 $ bit/sym），同时需要少于4千的存储空间。
Recent years have seen renewed attention to arithmetic coding (AC). This is thanks to the use of AC for distribution matching (DM) to control the channel input distribution in probabilistic amplitude shaping. There are two main problems inherent to AC: (1) its required arithmetic precision grows linearly with the input length, and (2) high-precision multiplications and divisions are required. Here, we introduce a multiplication-free AC-based DM technique via three lookup tables (LUTs) which solves both problems above. These LUTs are used to approximate the high-precision multiplications and divisions by additions and subtractions. The required precision of our approach is shown to grow logarithmically with the input length. We prove that this approximate technique maintains the invertibility of DM. At an input length of 1024 symbols, the proposed technique achieves negligible rate loss ($<0.01$ bit/sym) against the full-precision DM, while requiring less than 4 kilobytes of storage.
