ARQ with Doped Fountain Decoding

S. Kokalj-Filipovic, P. Spasojevic, E. Soljanin, R. Yates
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引用次数: 18

Abstract

We analyze the benefits of an automatic repeat- request (ARQ) scheme employed in doped belief-propagation decoding for increasing the throughput of fountain encoded data transmissions. The proposed doping mechanism selects doping symbols randomly from the set of input symbols contributing to degree-two output symbols. Here an output symbol is the encoded symbol whose code-graph links to input symbols decoded thus far have been severed. This doping approach always ensures releasing of at least one output symbol, thus increasing the number of degree-one output symbols (the ripple). Using a random walk analysis, we study the belief propagation decoding with degree-two random doping for a fountain code with symbols drawn from an Ideal Soliton distribution. We show that the decoding process is a renewal process whereas the process starts all over afresh after each doping. The approximate interdoping process analysis revolves around a random walk model for the ripple size. We model the sequence of the ripple size increments (due to doping and/or decoding) as an iid sequence of shifted and truncated Poisson random variables. This model furnishes a prediction on the number of required doping symbols and, furthermore, the ARQ throughput cost analysis. We also find that the Ideal Soliton significantly outperforms the Robust Soliton distribution in our ARQ-doping scheme.
ARQ与掺杂喷泉解码
本文分析了在掺杂信念传播译码中采用自动重复请求(ARQ)方案对提高喷泉编码数据传输吞吐量的好处。提出的掺杂机制从有助于二级输出的输入符号集中随机选择掺杂符号。这里的输出符号是已编码的符号,其代码图与已解码的输入符号的链接到目前为止已被切断。这种掺杂方法总是确保释放至少一个输出符号,从而增加一级输出符号(纹波)的数量。利用随机游走分析方法,研究了从理想孤子分布中提取符号的喷泉码的二阶随机掺杂信念传播译码。我们证明了解码过程是一个更新过程,而在每次掺杂后,这个过程都是重新开始的。近似的相互掺杂过程分析围绕着波纹大小的随机游走模型。我们将纹波大小增量序列(由于掺杂和/或解码)建模为移位和截断泊松随机变量的iid序列。该模型提供了所需掺杂符号数量的预测,并进一步进行了ARQ吞吐量成本分析。我们还发现,在arq掺杂方案中,理想孤子明显优于鲁棒孤子分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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