2008/02/05 by Brian M. Kurkoski, Kurkoski, Brian M., Justin Dauwels +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Algorithms and Data Compression #DNA and Biological Computing #Error Correcting Code Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.0802.0554
Cite this paper as: Brian Kurkoski and Justin Dauwels, "Message-passing decoding of lattices using Gaussian mixtures," in Proceedings of the 30th Symposium on Information Theory and its Applications (SITA 2007), pp. 877-882, November 27-30, 2007, Shima, Mie, Japan
arxiv created 2008/02/05 · openalex publication_date 2008/02/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A lattice decoder which represents messages explicitly as a mixture of Gaussians functions is given. In order to prevent the number of functions in a mixture from growing as the decoder iterations progress, a method for replacing N Gaussian functions with M Gaussian functions, with M < N, is given. A squared distance metric is used to select functions for combining. A pair of selected Gaussians is replaced by a single Gaussian with the same first and second moments. The metric can be computed efficiently, and at the same time, the proposed algorithm empirically gives good results, for example, a dimension 100 lattice has a loss of 0.2 dB in signal-to-noise ratio at a probability of symbol error of 10-5.