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 mixture elements 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. When used for the "Poltyrev system", the proposed algorithm achieves error rates close to that of the quantized implementation used in prior work. For example, for a dimension 1000 lattice, the difference in error rate is indistinguishable over a range of signal-to-noise ratios.

• Type: Journal
• Year: 2008
• Where: CORR
• Authors: Brian M. Kurkoski, Justin Dauwels
• Keywords: Belief-propagation Decoder, CORR 2008, Education, Error Rate, Low-density Lattice Codes