哈尔滨工程大学学报2009，Vol.30Issue(10)：1170-1174,5.DOI:10.3969/j.issn.1006-7043.2009.10.016
一种提高SCCC系统迭代检测收敛性的方法
A method to improve iterative decoding convergence in SCCC
摘要
Abstract
Iterative decoding based on the turbo principle is a novel approach for improving the performance of serial concatenated convolutional code (SCCC) systems. The speed of convergence of iterative detection is one of the key factors determining system performance. To reduce the high levels of feedback required during iterative decoding of short data blocks, a solution that improves the exchange of extrinsic information was proposed. In this method, inter decoder feedback is reduced by weighting the probability of extrinsic information between the inner and outer decoders. Theoretical analysis and simulation results show that the proposed method decreases the need for feedback and improves bit error rate performance. As a result, the average number of iterations was reduced and real time performance improved. In addition, the proposed method does not require conversion from probability to likelihood ratios, nor its inversion in the process of transforming extrinsic information. This significantly decreases the complexity of the decoding algorithm.关键词
串行级联卷积码/加权外信息/收敛性/迭代检测Key words
serially concatenated convolutional code/ weighted extrinsic information/ convergence/ iterative detection分类
信息技术与安全科学引用本文复制引用
赵旦峰,薛睿,苗延辉..一种提高SCCC系统迭代检测收敛性的方法[J].哈尔滨工程大学学报,2009,30(10):1170-1174,5.基金项目
"十一五"国防预研资助项目(4010607010102). （4010607010102）
