Generalized Mutual Information-Maximizing Quantized Decoding of LDPC Codes

11/26/2020
by   Peng Kang, et al.
0

In this paper, we propose a general framework of the mutual infomration-maximizing (MIM) quantized decoding for low-density parity-check (LDPC) codes, which can outperform the state-of-the-art lookup table (LUT) decoder by using simple mappings and fixed-point additions for the node updates. Our decoding method is generic in the sense that it can be applied to LDPC codes with arbitrary degree distributions, and it can be implemented based on either the belief propagation (BP) algorithm or the min-sum (MS) algorithm, leading to the MIM quantized BP (MIM-QBP) decoder and the MIM quantized MS (MIM-QMS) decoder, respectively. In particular, we approximate the check node (CN) update of the MIM-QBP decoder by a max-product operation and obtain the MIM-QMS decoder, which simplifies the decoder design and requires less resource consumption. To avoid the precision degradation, we introduce a dynamic reconstruction method to optimize the variable node update for different iterations. Some practical aspects of the proposed decoders such as the design and decoding complexity are also discussed. Simulation results show that the MIM-QBP decoder outperforms the LUT decoders in the waterfall region with both 3-bit and 4-bit precision. Moreover, the 4-bit MIM-QMS decoder can even surpass the floating-point BP decoder in the error-floor region.

READ FULL TEXT
research
04/14/2019

Mutual Information-Maximizing Quantized Belief Propagation Decoding of LDPC Codes

A severe problem for mutual information-maximizing lookup table (MIM-LUT...
research
05/14/2020

A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding

In this paper, we propose a finite-precision decoding method that featur...
research
11/13/2022

A Variable Node Design with Check Node Aware Quantization Leveraging 2-Bit LDPC Decoding

For improving coarsely quantized decoding of LDPC codes, we propose a ch...
research
02/07/2021

Learning to Decode Protograph LDPC Codes

The recent development of deep learning methods provides a new approach ...
research
01/16/2022

Memory Efficient Mutual Information-Maximizing Quantized Min-Sum Decoding for Rate-Compatible LDPC Codes

In this letter, we propose a two-stage design method to construct memory...
research
02/22/2021

Belief-Propagation Decoding of LDPC Codes with Variable Node-Centric Dynamic Schedules

Belief propagation (BP) decoding of low-density parity-check (LDPC) code...
research
11/07/2019

Performance Bounds and Estimates for Quantized LDPC Decoders

The performance of low-density parity-check (LDPC) codes at high signal-...

Please sign up or login with your details

Forgot password? Click here to reset