Quantized Message Passing for LDPC Codes

TL;DR

This paper introduces a quantized decoding algorithm for LDPC codes that uses LUTs designed via information theory, achieving better error rates with low message resolution compared to traditional decoders.

Contribution

It presents a novel LUT-based quantized decoding method for LDPC codes, improving performance at low message resolutions and analyzing design parameter effects.

Findings

Achieves better error rates with 3-bit messages than floating-point min-sum decoders.

Design SNR and LUT structure significantly impact decoder performance.

Proposes complexity reduction techniques like LUT re-use and message downsizing.

Abstract

We propose a quantized decoding algorithm for low- density parity-check codes where the variable node update rule of the standard min-sum algorithm is replaced with a look-up table (LUT) that is designed using an information-theoretic criterion. We show that even with message resolutions as low as 3 bits, the proposed algorithm can achieve better error rates than a floating-point min-sum decoder. Moreover, we study in detail the effect of different decoder design parameters, like the design SNR and the LUT tree structure on the performance of our decoder, and we propose some complexity reduction techniques, such as LUT re-use and message alphabet downsizing.