Granular gain of low-dimensional lattices based on binary linear codes is estimated using a quantization algorithm which is equivalently a soft-decision decoding of the underlying code. It is shown that substantial portion of the ultimate granular gain is achieved even in limited dimensions.
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Misako KOTANI, Shingo KAWAMOTO, Motohiko ISAKA, "Granular Gain of Low-Dimensional Lattices from Binary Linear Codes" in IEICE TRANSACTIONS on Fundamentals,
vol. E95-A, no. 12, pp. 2168-2170, December 2012, doi: 10.1587/transfun.E95.A.2168.
Abstract: Granular gain of low-dimensional lattices based on binary linear codes is estimated using a quantization algorithm which is equivalently a soft-decision decoding of the underlying code. It is shown that substantial portion of the ultimate granular gain is achieved even in limited dimensions.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E95.A.2168/_p
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@ARTICLE{e95-a_12_2168,
author={Misako KOTANI, Shingo KAWAMOTO, Motohiko ISAKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Granular Gain of Low-Dimensional Lattices from Binary Linear Codes},
year={2012},
volume={E95-A},
number={12},
pages={2168-2170},
abstract={Granular gain of low-dimensional lattices based on binary linear codes is estimated using a quantization algorithm which is equivalently a soft-decision decoding of the underlying code. It is shown that substantial portion of the ultimate granular gain is achieved even in limited dimensions.},
keywords={},
doi={10.1587/transfun.E95.A.2168},
ISSN={1745-1337},
month={December},}
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TY - JOUR
TI - Granular Gain of Low-Dimensional Lattices from Binary Linear Codes
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2168
EP - 2170
AU - Misako KOTANI
AU - Shingo KAWAMOTO
AU - Motohiko ISAKA
PY - 2012
DO - 10.1587/transfun.E95.A.2168
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E95-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2012
AB - Granular gain of low-dimensional lattices based on binary linear codes is estimated using a quantization algorithm which is equivalently a soft-decision decoding of the underlying code. It is shown that substantial portion of the ultimate granular gain is achieved even in limited dimensions.
ER -