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Nested quantization and Slepian-Wolf coding: a Wyner-Ziv coding paradigm for i.i.d. sources

机译:嵌套量化和Slepian-Wolf编码:i.i.d的Wyner-Ziv编码范例资料来源

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A new paradigm for Wyner-Ziv coding of i.i.d. sources is proposed that consists of nested quantization and Slepian-Wolf coding. The former plays the role of quantization with side information (at the decoder) and the latter lossless coding with side information. The proposed Slepian-Wolf coded nested quantization (SWC-NQ) framework generalizes the classic source coding approach of quantization and lossless/entropy coding. The main thrust is to treat Wyner-Ziv coding as a source-channel coding problem in which the side information is taken into account in the channel coding component via binning. For Gaussian sources with MSE measure, assuming nested lattice quantization with ideal Slepian-Wolf coding and high rate, we establish system performance bounds of SWC-NQ similar to those in classic source coding, showing that 1-D/2-D nested lattice quantization performs 1.53/1.36 dB worse than the Wyner-Ziv distortion-rate function D/sub WZ/{R). Using nested lattices in higher dimensions or nested trellis-coded quantization (TCQ) could possibly approach D/sub WZ/(R) even further. We implement 1-D and 2-D nested lattice quantization, together with irregular low-density parity-check (LDPC) codes for Slepian-Wolf coding, obtaining performance close to the corresponding theoretical limits.
机译:i.i.d.的Wyner-Ziv编码的新范例提出了由嵌套量化和Slepian-Wolf编码组成的源。前者起辅助信息的量化作用(在解码器处),而后者起辅助信息的无损编码的作用。提出的Slepian-Wolf编码嵌套量化(SWC-NQ)框架概括了量化和无损/熵编码的经典源编码方法。主要目的是将Wyner-Ziv编码视为源信道编码问题,其中通过合并在信道编码组件中考虑了边信息。对于具有MSE度量的高斯源,假设采用理想的Slepian-Wolf编码和高速率进行嵌套晶格量化,我们建立了与经典源编码相似的SWC-NQ的系统性能范围,表明1-D / 2-D嵌套晶格量化比Wyner-Ziv失真率函数D / sub WZ / {R)差1.53 / 1.36 dB。使用更高维度的嵌套晶格或嵌套网格编码量化(TCQ)可能甚至更接近D / sub WZ /(R)。我们将一维和二维嵌套晶格量化与不规则的低密度奇偶校验(LDPC)码一起用于Slepian-Wolf编码,从而获得接近相应理论极限的性能。

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