Reduced-Memory Decoding of Low-Density Lattice Codes
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Kurkoski-2010-Reduced-Memory Decod.pdf
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Author(s)
Kurkoski, Brian M.
Dauwels, Justin H. G.
Date Issued
July 2010
Journal
IEEE Communications Letters
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kurkoski, Brian, and Justin Dauwels. “Reduced-Memory Decoding of Low-Density Lattice Codes.” IEEE Communications Letters 14.7 (2010): 659–661. Web. © 2010 IEEE.
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1109/lcomm.2010.07.092350
