SCL-GRAND: Lower complexity and better flexibility for CRC-Polar Codes

Guessing random additive noise decoding (GRAND) is a recently proposed decoding algorithm which can achieve the error performance of maximum likelihood (ML) decoding. However, GRAND and its variants are only suitable for some short codes with high code rates and have large average query numbers. To...

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Bibliographic Details
Published in2023 IEEE Wireless Communications and Networking Conference (WCNC) pp. 1 - 5
Main Authors Li, Xuanyu, Niu, Kai, Dai, Jincheng, Tan, Zhiyuan, Guo, Zhiheng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2023
Subjects
Additive noise
Channel Coding
Codes
Complexity theory
CRC-Polar
Cyclic redundancy check
GRAND
Maximum likelihood decoding
SCL
Signal to noise ratio
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Summary:Guessing random additive noise decoding (GRAND) is a recently proposed decoding algorithm which can achieve the error performance of maximum likelihood (ML) decoding. However, GRAND and its variants are only suitable for some short codes with high code rates and have large average query numbers. To mitigate these problems, we propose a successive cancellation list (SCL)-GRAND decoding algorithm for the cyclic redundancy check concatenated polar (CRC-polar) codes. The proposed decoder first divides the received sequence into two subblocks. Then SCL is used to decode the upper subblock and output several candidates into the candidate list. For each candidate, GRAND is used to decode the lower subblock and finally choose the most-likely codeword as the decoded result. Since the SCL is integrated into the SCL-GRAND algorithm, this algorithm can achieve lower complexity and better flexibility than the original GRAND.
ISSN:1558-2612
DOI:10.1109/WCNC55385.2023.10118689