解码方法
计算机科学
涡轮
规范化(社会学)
Turbo码
直方图
算法
吞吐量
误码率
串行级联卷积码
提前停车
涡轮均衡器
低密度奇偶校验码
人工智能
级联纠错码
无线
图像(数学)
错误层
电信
工程类
区块代码
汽车工程
人工神经网络
人类学
社会学
作者
Imed Amamra,Nadir Derouiche
标识
DOI:10.1109/melcon.2012.6196527
摘要
The present paper proposes an early stopping method for iterative turbo decoding. Many criterions were proposed to date, motivated by a variety of reasons, such as increasing average decoding throughput or reducing average decoder power consumption. The method is devised on observing the behavior of LLR (Log-Likelihood Ratio). Simulation results in comparing the proposed method with some normalization techniques show that our method achieves an acceptable BER (Bit Error Rate) performance and reduces considerably the average number of iterations.
科研通智能强力驱动
Strongly Powered by AbleSci AI