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arXiv cs/0701103cs.ITmath.IT
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基于信息内容进化的Raptor码联合译码分析与设计

Analysis and design of raptor codes for joint decoding using Information Content evolution

Auguste Venkiah, Charly Poulliat, David Declercq

摘要:

本文分析了在二进制输入加性白噪声信道(BIAWGNC)下Raptor码在联合译码下的收敛性,并给出了一种优化方法。我们使用高斯近似下的信息内容进化,并专注于一个新的解码方案,证明是更有效的:联合解码的两个代码组件的猛禽码。在我们的一般模型中,经典的级联译码方案似乎是一个子情况,因此,LT码的设计也是可能的。

英文摘要:

In this paper, we present an analytical analysis of the convergence of raptor codes under joint decoding over the binary input additive white noise channel (BIAWGNC), and derive an optimization method. We use Information Content evolution under Gaussian approximation, and focus on a new decoding scheme that proves to be more efficient: the joint decoding of the two code components of the raptor code. In our general model, the classical tandem decoding scheme appears to be a subcase, and thus, the design of LT codes is also possible.

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。

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