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Distributed Source Coding Using Abelian Group Codes: A New Achievable Rate-Distortion Region

机译:使用阿贝尔群码的分布式源编码:一个新的可实现的速率失真区域

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A distributed source coding problem with a joint distortion criterion that depends on the sources and the reconstruction is considered in this work. While the prevalent trend in information theory has been to prove achievability results using Shannon''s random coding arguments, using structured random codes offer rate gains over unstructured random codes for many problems. Motivated by this, a new achievable rate-distortion region (an inner bound to the performance limit) is presented for this problem for discrete memoryless sources based on “good” structured random nested codes built over abelian groups. For certain sources and distortion functions, the new rate region is shown to be strictly bigger than the Berger-Tung rate region, which has been the best known achievable rate region for this problem till now. This is done using numerical plots. Achievable rates for single-user source coding using abelian group codes are also obtained as a corollary of the main coding theorem. It is shown that nested linear codes achieve the Shannon rate-distortion function in the arbitrary discrete memoryless case.
机译:在这项工作中考虑了具有联合失真标准的分布式源编码问题,该联合失真标准取决于源和重构。尽管信息理论的流行趋势是使用Shannon的随机编码参数来证明可实现性的结果,但是在许多问题上,使用结构化随机码会比非结构化随机码提供更高的速率。以此为动机,针对离散无记忆源,基于建立在阿贝尔群上的“良好”结构化随机嵌套代码,针对此问题提出了一个新的可实现的速率失真区域(性能极限的内部界限)。对于某些信号源和失真函数,新速率区域显示出严格大于Berger-Tung速率区域,该区域迄今为止是该问题最著名的可实现速率区域。这是使用数字图完成的。作为主编码定理的推论,也获得了使用阿贝尔群码的单用户源编码的可实现速率。结果表明,在任意离散无记忆情况下,嵌套线性码都能实现香农率失真功能。

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