.png){kind=icon}
返回
A constraint-length based modified Viterbi algorithm with adaptive effort
.png){kind=icon}
PRE
AI
DOI：10.1109/26.803492.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A modified Viterbi algorithm for convolutional codes is described that provides for signal-to-noise ratio (SNR) adaptive computational effort. The algorithm has three levels of prioritized effort. Movement from one level to the next is controlled by parameters that can be selected according to desired output bit-error-rate performance. For 3-bit soft decision detected signals, coding gain within 0.06 dB of Viterbi at 3-dB SNR is achieved for the same constraint-length code with modest parameter values and computational effort. At values of SNR above 6 dB, the algorithm decodes with very low computational effort. Effort levels are controlled by spanning the decoding trellis in steps that are one constraint-length long.
Keyword:
CONVOLUTIONAL-CODES
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
IF:
8.3
论文数:
1.2W
被引数:
3.6W
机构
暂无机构信息
引用论文
分享收藏The relationship between AGT self‐description and significant life events: A longitudinal study
PREAI
分享收藏分享收藏Structural Basis of the Ferrous Iron Specificity of the Yeast Ferroxidase, Fet3p.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏 没有更多内容
没有更多内容