Reduced-Memory Decoding of Low-Density Lattice Codes

This letter describes a belief-propagation decoder for low-density lattice codes of finite dimension, in which the messages are represented as single Gaussian functions. Compared to previously-proposed decoders, memory is reduced because each message consists of only two values, the mean and varianc...

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Bibliographic Details
Published in:IEEE communications letters 2010-07, Vol.14 (7), p.659-661
Main Authors: Kurkoski, B, Dauwels, J
Format: Article
Language:English
Subjects:
Applied sciences
Approximation
belief-propagation decoding
Channel capacity
Coding, codes
Decoders
Decoding
Educational technology
Exact sciences and technology
Gaussian
Gaussian noise
Information, signal and communications theory
lattice decoding
Lattices
Low-density lattice codes
Mathematical analysis
Messages
Noise levels
Parity check codes
Signal and communications theory
Telecommunications and information theory
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Summary:This letter describes a belief-propagation decoder for low-density lattice codes of finite dimension, in which the messages are represented as single Gaussian functions. Compared to previously-proposed decoders, memory is reduced because each message consists of only two values, the mean and variance. Complexity is also reduced because the check node operations are on single Gaussians, avoiding approximations needed previously, and because the variable node performs approximations on a smaller number of Gaussians. For lattice dimension n = 1000 and 10,000, this decoder looses no more than 0.1 dB in SNR, compared to the decoders which use much more memory.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2010.07.092350