Title
Serially Concatenated Scheme Of Polar Codes And The Improved Belief Propagation Decoding Algorithm
Abstract
In this study, a serially concatenated scheme of polar codes with convolutional codes is proposed to improve the error correction performance. The novel belief propagation (BP) decoding algorithm addresses two issues that are present in the currently available BP decoding algorithms. The first issue is the poor performance of the BP decoding algorithms, in particular the introduction of an error floor. The second is the component codes can only use systematic codes in the traditional concatenated scheme of polar codes with convolutional codes, which inhibits the effective update of the prior information of the redundant check bits. The proposed BP decoding algorithm is based on right-directed message processing, which effectively improves the decoding performance. In addition, the proposed concatenated scheme extends the selection of component codes from the systematic polar codes to the non-systematic polar codes. Hence, the areas of applications and the prior information of information bits for polar codes are expanded and more effectively updated, respectively. The simulation results show that the proposed scheme is much better than the traditional concatenated scheme, and the error floor is no longer introduced in terms of the block error rate, while the storage and computational complexities have not increased obviously.
Year
DOI
Venue
2020
10.1049/iet-com.2019.0887
IET COMMUNICATIONS
Keywords
DocType
Volume
convolutional codes, computational complexity, iterative decoding, concatenated codes, polar codes, belief propagation, concatenation codes, belief propagation algorithm, component codes, convolutional codes, decoding performance, systematic polar codes, nonsystematic polar codes, serially concatenated scheme, novel BP decoding algorithm
Journal
14
Issue
ISSN
Citations 
14
1751-8628
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yinyou Mao100.34
Dong Yang211618.09
Xingcheng Liu36617.47
Yi Xie411.04