Soft-Bit Decoding of Regular Low-Density Parity-Check Codes

Sheryl L. Howard; Vincent C. Gaudet; Christian Schlegel

doi:10.1109/TCSII.2005.850742

Soft-Bit Decoding of Regular Low-Density Parity-Check Codes

Sheryl L. Howard, Vincent C. Gaudet, Christian Schlegel

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

A novel representation, using soft-bit messages, of the belief propagation (BP) decoding algorithm for low-density parity-check codes is derived as an alternative to the log-likeli-hood-ratio (LLR)-based BP and min-sum decoding algorithms. A simple approximation is also presented. Simulation results demonstrate the functionality of the soft-bit decoding algorithm. Floating-point soft-bit and LLR BP decoding show equivalent performance; the approximation incurs 0.5-dB loss, comparable to min-sum performance loss over BP. Fixed-point results show similar performance to LLR BP decoding; the approximation converges to floating-point results with one less bit of precision.

Original language	English (US)
Pages (from-to)	646-650
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	52
Issue number	10
DOIs	https://doi.org/10.1109/TCSII.2005.850742
State	Published - Oct 2005
Externally published	Yes

Keywords

Belief propagation (BP)
iterative decoding algorithms
low-density parity-check (LDPC) codes
soft output decoding

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/TCSII.2005.850742

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title = "Soft-Bit Decoding of Regular Low-Density Parity-Check Codes",

abstract = "A novel representation, using soft-bit messages, of the belief propagation (BP) decoding algorithm for low-density parity-check codes is derived as an alternative to the log-likeli-hood-ratio (LLR)-based BP and min-sum decoding algorithms. A simple approximation is also presented. Simulation results demonstrate the functionality of the soft-bit decoding algorithm. Floating-point soft-bit and LLR BP decoding show equivalent performance; the approximation incurs 0.5-dB loss, comparable to min-sum performance loss over BP. Fixed-point results show similar performance to LLR BP decoding; the approximation converges to floating-point results with one less bit of precision.",

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