.png){kind=icon}
返回
A modified Min Sum decoding algorithm based on LMMSE for LDPC codes
.png){kind=icon}
PRE
AI
DOI：10.1016/j.aeue.2014.04.024.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A new modified Min Sum decoding algorithm based on parameter estimation theory for Low Density Parity Check (LDPC) codes is presented in this paper. First, Linear Minimum Mean Square Error (LMMSE) estimate criterion is used to model the magnitude of check-to-variable message and calculate estimated parameters, furthermore the golden section search algorithm is used to speed up getting the boundary, with which the parameters can be determined. Then, the parameters are modified further on the basis of the relationship between the iteration number and the estimated parameters. Finally, the same estimated parameters are used for different signal to noise ratio (SNR) to ensure the decoding performance and reduce the hardware complexity. The simulation results show that a gain of 03-0.5 dB can be achieved in comparison with other kinds of modified Min Sum algorithms, which is very close to that of BP algorithm. What's more, the algorithm has the following characteristics: low computation complexity, small decoding delay, easiness of calculation for estimated parameters, and simplicity in hardware implementation. (C) 2014 Elsevier GmbH. All rights reserved.
Keyword:
LDPC
Min Sum decoding algorithm
LMMSE
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
A
IF:
3.2
论文数:
5.8K
被引数:
8.3K
机构
引用论文
Three-dimensional nanofabrication via ultrafast laser patterning and kinetically regulated material assembly通过超快激光图案化和动力学调节的材料组装进行三维纳米加工.png)
Science
OAAI
ScienceIF0
OAAI分享收藏Reduced complexity iterative decoding of low-density parity check codes based on belief propagation基于置信传播的低密度奇偶校验码迭代译码复杂度降低
PREAI
分享收藏
查看更多内容