We propose three effective approximate belief propagation decoders for polar codes using Maclaurin's series, piecewise linear function, and stepwise linear function. The proposed decoders have the better perfor-mance than that of existing approximate belief propagation polar decoders, min-sum decoder and normalized min-sum decoder, and almost the same performance with that of original belief propagation decoder. Moreover, the proposed decoders achieve such performance without any optimiza-tion process according to the code parameters and channel condition unlike normalized min-sum decoder, offset min-sum decoder, and their variants.
|Number of pages||4|
|Journal||IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences|
|Publication status||Published - 2017 Sep|
Bibliographical noteFunding Information:
Manuscript received March 25, 2017. †The authors are with the Yonsei University, Korea. ∗This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No.2016-0-00181, Development on the core technologies of transmission, modulation and coding with low-power and low-complexity for massive connectivity in the IoT environment). a) E-mail: firstname.lastname@example.org b) E-mail: email@example.com c) E-mail: firstname.lastname@example.org d) E-mail: email@example.com (Corresponding author) DOI: 10.1587/transfun.E100.A.2052
Copyright © 2017 The Institute of Electronics, Information and Communication Engineers.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics