Iterative Decoding of PCCC Base on Soft Input Hard Output

摘要：

The parallel concatenated convolutional code has excellent distance performance and this paper presents a new iterative decoding algorithm. The α (n) and β(n) sequences as the adjustment factors have been introduced in the feedback.Via the Viterbi decoding the decoder of the component codes outputs the hard decision information, which is combined with the received soft information doing linear processing with the help of the adjustment factors,and then the soft input of the decoder in the next level can be got. The values of the α(n) and β (n) sequences in the four iterations have been determined in the simulation experiment. Further experimental results show that compared with the product code, the PCCC has stronger error correction performance and faster decoding speed.

关键词： Parallel Concatenated ConvolutionalCodes Recursive Systematic Convolutional Codes Iterative Decoding Adjustment Factor

作者: Wanquan Peng Erjin Gao Xiaobing Wu

作者单位: Department of Electrical Engineering & Automation Chongqing Vocational Institute of Engineering Chongqing, China

会议类型: 国际会议

会议名称: 2012 International Conference on Electric Technology and Civil Engineering(2012 电子技术与土木工程国际会议 ICETCE 2012)

会议地点: 三峡

会议语种:英文

页码: 2485-2488

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）