4.6 Article

Does Gaussian Approximation Work Well for the Long-Length Polar Code Construction?

期刊

IEEE ACCESS
卷 5, 期 -, 页码 7950-7963

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2692241

关键词

Polar codes; Gaussian approximation (GA); polarization violation set (PVS); polarization reversal set (PRS); cumulative-logarithmic error (CLE)

资金

  1. National Natural Science Foundation of China [61671080, 61401037]
  2. BUPT-SICE
  3. Huawei HIRP

向作者/读者索取更多资源

Gaussian approximation (GA) is widely used to construct polar codes. However, when the code length is long, the subchannel selection inaccuracy due to the calculation error of conventional approximate GA (AGA), which uses a two-segment approximation function, results in a catastrophic performance loss. In this paper, new principles to design the GA approximation functions for polar codes are proposed. First, we introduce the concepts of polarization violation set (PVS) and polarization reversal set (PRS) to explain the essential reasons that the conventional AGA scheme cannot work well for the long-length polar code construction. In fact, these two sets will lead to the rank error of subsequent subchannels, which means that the orders of subchannels are misaligned, which is a severe problem for polar code construction. Second, we propose a new metric, named cumulative-logarithmic error (CLE), to quantitatively evaluate the remainder approximation error of AGA in the logarithm. We derive the upper bound of CLE to simplify its calculation. Finally, guided by PVS, PRS, and CLE bound analysis, we propose new construction rules based on a multi-segment approximation function, which obviously improve the calculation accuracy of AGA so as to ensure the excellent performance of polar codes especially for the long code lengths. Numerical and simulation results indicate that the proposed AGA schemes are critical to constructing high-performance polar codes.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据