Non-uniform quantization scheme for the decoding of low-density parity-check codes with the sum-product algorithm

Qu, Xinru; Yin, Liuguo

doi:10.1109/iceiec.2016.7589702

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Note that, for SPA-based algorithms, three major processes involving LDPC decoding are initialization, check node processing, and variable node processing [13]. By using the same quantization bits for all decoding processes, the fnite precision efects on LDPC decoding are investigated in [14].…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Rate-Compatible LDPC Codes under All-Integer Quantization Decoding

Muangkammuen

Vongjampa

Suthisopapan

2022

Journal of Electrical and Computer Engineering

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From a practical point of view, quantization is necessary for the design of any low-complexity LDPC decoder. However, the quantization scheme with the minimum computational complexity called all-integer quantization has not been well investigated since, intuitively, it seems to significantly degrade the decoding performance. It is found in this work that the utilization of 4-bit all-integer quantization for MSA-based LDPC decoder is adequate to achieve the decoding performance of the nonquantized case which can be considered as the lower bound on the decoding performance. Moreover, this simple quantization scheme can also be applied to the hardware and cost-efficient rate-compatible LDPC codes.

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Section: Introductionmentioning

confidence: 99%

On the Performance of Rate-Compatible LDPC Codes under All-Integer Quantization Decoding

Muangkammuen

Vongjampa

Suthisopapan

2022

Journal of Electrical and Computer Engineering

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“…While similar in operation to the lookup tables developed for the FAID approach [4], [5], the tables used in information bottleneck (IB) decoders are designed analytically [11]- [15]. Maximizing mutual information requires access to the respective joint distributions in each decoder iteration.…”

Section: Introductionmentioning

confidence: 99%

Decoding Rate-Compatible 5G-LDPC Codes With Coarse Quantization Using the Information Bottleneck Method

Stark

Wang

Bauch

et al. 2020

IEEE Open J. Commun. Soc.

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Increased data rates and very low-latency requirements place strict constraints on the computational complexity of channel decoders in the new 5G communications standard. Practical low-density parity-check (LDPC) decoder implementations use message-passing decoding with finite precision, which becomes coarse as complexity is more severely constrained. In turn, performance degrades as the precision becomes more coarse. Recently, the information bottleneck (IB) method was used to design mutual-information-maximizing mappings that replace conventional finite-precision node computations. As a result, the exchanged messages in the IB approach can be represented with a very small number of bits. 5G LDPC codes have the so-called protograph-based raptor-like (PBRL) structure which offers inherent rate-compatibility and excellent performance. This paper extends the IB principle to the flexible class of PBRL LDPC codes as standardized in 5G. The extensions include IB decoder design for puncturing and rate-compatibility. In contrast to existing IB decoder design techniques, the proposed decoder can be used for a large range of code rates with a static set of optimized mappings. The proposed construction approach is evaluated for a typical range of code rates and bit resolutions ranging from 3 bit to 5 bit. Frame error rate simulations show that the proposed scheme always outperforms min-sum decoding algorithms and operates close to double-precision sum-product belief propagation decoding. Furthermore, alternatives to the lookup table implementations of the mutual-information-maximizing mappings are investigated. INDEX TERMS LDPC codes, 5G, message-passing decoding, mutual-information based signal processing, information bottleneck method, machine learning.

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A Low-Complexity Decoder With Non-Uniform Quantization for Recursive BMST Codes

Zhao

2021

IEEE Commun. Lett.

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Non-uniform quantization scheme for the decoding of low-density parity-check codes with the sum-product algorithm

Cited by 3 publications

References 8 publications

On the Performance of Rate-Compatible LDPC Codes under All-Integer Quantization Decoding

On the Performance of Rate-Compatible LDPC Codes under All-Integer Quantization Decoding

Decoding Rate-Compatible 5G-LDPC Codes With Coarse Quantization Using the Information Bottleneck Method

A Low-Complexity Decoder With Non-Uniform Quantization for Recursive BMST Codes

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