极格有利于有损压缩

Ling Liu, Cong Ling
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引用次数: 8

摘要

由极码构造的极格最近被证明能够实现加性高斯白噪声信道的容量。在这项工作中,我们证明了极格也可以解决对偶问题,即实现无记忆高斯源的速率失真界,这意味着极格也可以很好地用于连续源的有损压缩。所提出的极格结构使我们能够将后熵编码过程集成到晶格量化器中,从而简化了量化过程。此外,极格的嵌套结构进一步为一些多端编码问题提供了解决方案。高斯源的Wyner-Ziv编码问题可以通过在速率失真界中嵌套极性晶格的AWGN容量来解决,而Gelfand-Pinsker问题可以以相反的方式解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Polar lattices are good for lossy compression
Polar lattices, which are constructed from polar codes, have recently been proved to be able to achieve the capacity of the additive white Gaussian noise (AWGN) channel. In this work, we show that polar lattices can also solve the dual problem, i.e., achieving the rate-distortion bound of a memoryless Gaussian source, which means that polar lattices can also be good for the lossy compression of continuous sources. The structure of the proposed polar lattices enables us to integrate the post-entropy coding process into the lattice quantizer, which simplifies the quantization process. Moreover, the nesting structure of polar lattices further provides solutions for some multi-terminal coding problems. The Wyner-Ziv coding problem for a Gaussian source can be solved by an AWGN capacity achieving polar lattice nested in a rate-distortion bound achieving one, and the Gelfand-Pinsker problem can be solved in a reversed manner.
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