Message-passing decoding of lattices using Gaussian mixtures

A belief-propagation decoder for low-density lattice codes, which represents messages explicitly as a mixture of Gaussians functions, is given. In order to prevent the number of functions from growing as the decoder iterations progress, a method for reducing the number of Gaussians at each step is given. A squared distance metric is used, which is shown to be a lower bound on the divergence. For an unconstrained power system, comparisons are made with a quantized implementation. For a dimension 100 lattice, a loss of about 0.2 dB was found; for dimension 1000 and 10000 lattices, the difference in error rate was indistinguishable. The memory required to store the messages is substantially superior to the quantized implementation.

• Publication year

  2008

• Venue

  2008 IEEE International Symposium on Information Theory

• Publication date

  2008-02-04

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/ISIT.2008.4595439arXiv 0802.0554
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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