On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes

The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance...

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Veröffentlicht in:IEEE transactions on communications Jg. 53; H. 4; S. 549 - 554
Hauptverfasser: Jianguang Zhao, Zarkeshvari, F., Banihashemi, A.H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.04.2005
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Additive white noise
Algorithms
Applied sciences
AWGN
Blocking
Broadband communication
Clipping
Coding, codes
Decibels
Decoding
Errors
Exact sciences and technology
Information, signal and communications theory
Iterative algorithms
Iterative decoding
iterative decoding algorithms
low-density parity-check (LDPC) codes
max-product algorithm
max-sum algorithm
min-sum algorithm
modified min-sum algorithms
Parity check codes
Quantization
Signal and communications theory
Signal to noise ratio
Systems engineering and theory
Telecommunications and information theory
Wireless communication
max-product algorithm
Quantization
min-sum algorithm
Iterative method
iterative decoding algorithms
Decoding
max-sum algorithm
Algorithm
modified min-sum algorithms
Simulation
low-density parity-check (LDPC) codes
Clipping
Parity check codes
ISSN:0090-6778, 1558-0857
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Beschreibung
Zusammenfassung:The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance over a wide range of signal-to-noise ratios. Moreover, we propose modifications to the min-sum algorithm that improve the performance by a few tenths of a decibel with just a small increase in decoding complexity. A quantized version of these modified algorithms is also studied. It is shown that, when optimized, modified quantized min-sum algorithms perform very close to, and in some cases even slightly outperform, the ideal belief-propagation algorithm at observed error rates.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2004.836563