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Laminated Turbo Codes: A New Class of Block-Convolutional Codes

机译:分层Turbo码:一类新的块卷积码

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摘要

In this paper, a new class of codes is presented that features a block-convolutional structure—namely, laminated turbo codes. It allows combining the advantages of both a convolutional encoder memory and a block permutor, thus allowing a block-oriented decoding method. Structural properties of laminated turbo codes are analyzed and upper and lower bounds on free distance are obtained. It is then shown that the performance of laminated turbo codes compares favorably with that of turbo codes. Finally, we show that laminated turbo codes provide high rate flexibility without suffering any significant performance degradation.
机译:在本文中,提出了一种具有块卷积结构的新型代码,即分层Turbo代码。它允许结合卷积编码器存储器和块置换器的优点,从而允许使用面向块的解码方法。分析了叠层turbo码的结构特性,得到了自由距离的上下限。然后表明层压的turbo码的性能与turbo码的性能相比是有利的。最后,我们证明了分层涡轮代码提供了高速率灵活性,而不会出现任何明显的性能下降。

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