Stochastic decoding for LDPC convolutional codes

Xin Ru Lee; Chih Lung Chen; Hsie-Chia Chang; Chen-Yi Lee

doi:10.1109/ISCAS.2012.6271843

Stochastic decoding for LDPC convolutional codes

Xin Ru Lee^*, Chih Lung Chen, Hsie-Chia Chang, Chen-Yi Lee

^*Corresponding author for this work

Department of Electronics Engineering

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

Among LDPC codes, LDPC convolutional codes (LDPC-CCs) seem to be more suitable for variable length applications. However, a LDPC-CC decoder is difficult to implement for its long latency and large storage usage. The stochastic computation makes the decoding of LDPC-CCs more efficient, but the boundary effect of sliding window causes poor performance. In this paper, a stochastic LDPC-CC decoder with virtual edge compensation as well as decoder architecture is presented. The simulation results based on (491, 3, 6) time-varying LDPC-CC show that under the same signal-to-noise ratio, our proposed decoder could achieve better performance, 60% less decoding latency and 40% storage reduction compared to log-BP decoder with 10 processors.

Original language	English
Pages	2621-2624
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2012.6271843
State	Published - 28 Sep 2012
Event	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, Korea, Republic of Duration: 20 May 2012 → 23 May 2012

Conference

Conference	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
Country	Korea, Republic of
City	Seoul
Period	20/05/12 → 23/05/12

Keywords

LDPC convolutional codes
stochastic decoding

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10.1109/ISCAS.2012.6271843

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title = "Stochastic decoding for LDPC convolutional codes",

abstract = "Among LDPC codes, LDPC convolutional codes (LDPC-CCs) seem to be more suitable for variable length applications. However, a LDPC-CC decoder is difficult to implement for its long latency and large storage usage. The stochastic computation makes the decoding of LDPC-CCs more efficient, but the boundary effect of sliding window causes poor performance. In this paper, a stochastic LDPC-CC decoder with virtual edge compensation as well as decoder architecture is presented. The simulation results based on (491, 3, 6) time-varying LDPC-CC show that under the same signal-to-noise ratio, our proposed decoder could achieve better performance, 60% less decoding latency and 40% storage reduction compared to log-BP decoder with 10 processors.",

keywords = "LDPC convolutional codes, stochastic decoding",

author = "Lee, {Xin Ru} and Chen, {Chih Lung} and Hsie-Chia Chang and Chen-Yi Lee",

year = "2012",

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day = "28",

doi = "10.1109/ISCAS.2012.6271843",

language = "English",

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T1 - Stochastic decoding for LDPC convolutional codes

AU - Lee, Xin Ru

AU - Chen, Chih Lung

AU - Chang, Hsie-Chia

AU - Lee, Chen-Yi

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N2 - Among LDPC codes, LDPC convolutional codes (LDPC-CCs) seem to be more suitable for variable length applications. However, a LDPC-CC decoder is difficult to implement for its long latency and large storage usage. The stochastic computation makes the decoding of LDPC-CCs more efficient, but the boundary effect of sliding window causes poor performance. In this paper, a stochastic LDPC-CC decoder with virtual edge compensation as well as decoder architecture is presented. The simulation results based on (491, 3, 6) time-varying LDPC-CC show that under the same signal-to-noise ratio, our proposed decoder could achieve better performance, 60% less decoding latency and 40% storage reduction compared to log-BP decoder with 10 processors.

AB - Among LDPC codes, LDPC convolutional codes (LDPC-CCs) seem to be more suitable for variable length applications. However, a LDPC-CC decoder is difficult to implement for its long latency and large storage usage. The stochastic computation makes the decoding of LDPC-CCs more efficient, but the boundary effect of sliding window causes poor performance. In this paper, a stochastic LDPC-CC decoder with virtual edge compensation as well as decoder architecture is presented. The simulation results based on (491, 3, 6) time-varying LDPC-CC show that under the same signal-to-noise ratio, our proposed decoder could achieve better performance, 60% less decoding latency and 40% storage reduction compared to log-BP decoder with 10 processors.

KW - LDPC convolutional codes

KW - stochastic decoding

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