Region-Specific Coarse Quantization with Check Node Awareness in 5G-LDPC
  Decoding

This paper presents novel techniques for improving the error correction performance and reducing the complexity of coarsely quantized 5G-LDPC decoders. The proposed decoder design supports arbitrary message-passing schedules on a base-matrix level by modeling exchanged messages with entry-specific discrete random variables. Variable nodes (VNs) and check nodes (CNs) involve compression operations designed using the information bottleneck method to maximize preserved mutual information between code bits and quantized messages. We introduce alignment regions that assign the messages to groups with aligned reliability levels to decrease the number of individual design parameters. Group compositions with degree-specific separation of messages improve performance by up to 0.4 dB. Further, we generalize our recently proposed CN-aware quantizer design to irregular LDPC codes and layered schedules. The method optimizes the VN quantizer to maximize preserved mutual information at the output of the subsequent CN update, enhancing performance by up to 0.2 dB. A schedule optimization modifies the order of layer updates, reducing the average iteration count by up to 35 %. We integrate all new techniques in a rate-compatible decoder design by extending the alignment regions along a rate-dimension. Our complexity analysis for 2-bit decoding estimates up to 64 % higher throughput versus 4-bit decoding at similar performance.

Subjects

cs.IT

math.IT

LDPC decoding

layered schedule

rate-compatible

coarse quantization

information bottleneck

5G

DDC Class

621: Applied Physics

004: Computer Sciences

519: Applied Mathematics, Probabilities

Publication version

submittedVersion

Lizenz

https://creativecommons.org/licenses/by/4.0/

Name

2024 - Region Specific Coarse Quantization - Mohr_ARXIV.pdf

Type

Main Article

Size

1.65 MB

Format

Adobe PDF

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Region-Specific Coarse Quantization with Check Node Awareness in 5G-LDPC Decoding