arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1109.3876cs.ITmath.IT
收藏

二维的咬尾卷积码

Two-Dimensional Tail-Biting Convolutional Codes

Liam Alfandary, Dan Raphaeli

摘要:

多维卷积码是卷积码(CC)的概念到时间的若干维度的扩展。本文主要从几个方面对二维的【形】卷积码和二维咬尾卷积码进行了研究。首先,我们推导出这些代码的几个基本的代数性质,应用代数方法,以找到双射编码器,创建奇偶检验矩阵和逆编码器。接下来,我们讨论这些代码的最小距离和权重分布特性。扩展现有的树搜索算法的二维,我们将其应用到寻找代码与高的最小距离。文中给出了样本码的误码率渐近线,并与其它码进行了比较。这种方法的结果表明,2D TBCC可以比类似的1D TBCC或其他代码执行得更好。然后,我们提出了几种新的迭代次优算法的软解码二维CC,这是基于置信传播。两种主要的解码方法被认为是。我们首先集中在一个解码器,它扩展了网格解码的概念到两个维度。其次,我们调查的算法,使用代码的奇偶检验矩阵。我们应用传统的BP在奇偶域,但改进了它与一个新的修改。接下来,我们测试广义置信传播(GBP)算法。性能结果,并与最佳解码技术和界限。结果表明,我们的次优算法取得了令人尊敬的结果,在某些情况下,接近0.2dB的最佳(最大似然)解码。然而,对于一些代码仍然有一个很大的差距,从最佳解码器。

英文摘要:

The multidimensional convolutional codes are an extension of the notion of convolutional codes (CCs) to several dimensions of time. This paper explores the class of two-dimensional convolutional codes (2D CCs) and 2D tail-biting convolutional codes (2D TBCCs), in particular, from several aspects. First, we derive several basic algebraic properties of these codes, applying algebraic methods in order to find bijective encoders, create parity check matrices and to inverse encoders. Next, we discuss the minimum distance and weight distribution properties of these codes. Extending an existing tree-search algorithm to two dimensions, we apply it to find codes with high minimum distance. Word-error probability asymptotes for sample codes are given and compared with other codes. The results of this approach suggest that 2D TBCCs can perform better than comparable 1D TBCCs or other codes. We then present several novel iterative suboptimal algorithms for soft decoding 2D CCs, which are based on belief propagation. Two main approaches to decoding are considered. We first focus on a decoder which extends the concept of trellis decoding to two dimensions. Second, we investigate algorithms which use the code's parity check matrices. We apply conventional BP in the parity domain, but improve it with a novel modification. Next, we test the generalized belief propagation (GBP) algorithm. Performance results are presented and compared with optimum decoding techniques and bounds. The results show that our suboptimal algorithms achieve respectable results, in some cases coming as close as 0.2dB from optimal (maximum-likelihood) decoding. However for some of the codes there is still a large gap from the optimal decoder.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑