Memory-Assisted Quantized LDPC Decoding

We enhance coarsely quantized LDPC decoding by reusing computed check node messages from previous iterations. Typically, variable and check nodes update and replace old messages every iteration. We show that, under coarse quantization, discarding old messages entails a significant loss of mutual inf...

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Bibliographic Details
Published inIEEE communications letters Vol. 29; no. 5; pp. 888 - 892
Main Authors Mohr, Philipp, Bauch, Gerhard
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
5G mobile communication
5G NR
Algorithms
coarse quantization
Complexity theory
Decoding
information bottleneck
Iterative decoding
layered schedule
LDPC
Memory management
message passing
Messages
Mutual information
Optimization
Quantization (signal)
Random variables
Reliability
Online AccessGet full text
ISSN1089-7798
2373-7891
1558-2558
1558-2558
DOI10.1109/LCOMM.2025.3540277

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Summary:We enhance coarsely quantized LDPC decoding by reusing computed check node messages from previous iterations. Typically, variable and check nodes update and replace old messages every iteration. We show that, under coarse quantization, discarding old messages entails a significant loss of mutual information. The loss is avoided with additional memory, improving performance by up to 0.23 dB. We optimize quantization with a modified information bottleneck algorithm that considers the statistics of old messages. A simple merge operation reduces memory requirements. Depending on channel conditions and code rate, memory assistance enables up to 32% better area efficiency for 2-bit decoding.
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ISSN:1089-7798
2373-7891
1558-2558
1558-2558
DOI:10.1109/LCOMM.2025.3540277