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 in:IEEE communications letters Vol. 29; no. 5; pp. 888 - 892
Main Authors: Mohr, Philipp, Bauch, Gerhard
Format: Journal Article
Language:English
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
ISSN:1089-7798, 1558-2558
Online Access:Get full text
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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
1558-2558
DOI:10.1109/LCOMM.2025.3540277