Improved Bit-Flipping Algorithm for Successive Cancellation Decoding of Polar Codes

The interest in polar codes has been increasing significantly since their adoption for use in the 5 th generation wireless systems standard. Successive cancellation (SC) decoding algorithm has low implementation complexity, but yields mediocre error-correction performance at the code lengths of inte...

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Bibliographic Details
Published in:IEEE transactions on communications Vol. 67; no. 1; pp. 61 - 72
Main Authors: Ercan, Furkan, Condo, Carlo, Gross, Warren J.
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
5G mobile communication
Algorithms
Channels
Classification
Complexity
Computer simulation
Decoding
Encoding
Error analysis
Error correction
error-correction performance
Estimation
Frequency estimation
Iterative decoding
Likelihood ratio
Matching
Polar codes
Reliability
SC-Flip decoding
Sorting algorithms
ISSN:0090-6778, 1558-0857
Online Access:Get full text
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Summary:The interest in polar codes has been increasing significantly since their adoption for use in the 5 th generation wireless systems standard. Successive cancellation (SC) decoding algorithm has low implementation complexity, but yields mediocre error-correction performance at the code lengths of interest. SC-Flip algorithm improves the error-correction performance of SC by identifying possibly erroneous decisions made by SC and re-iterates after flipping one bit. It was recently shown that only a portion of bit-channels are most likely to be in error. In this paper, we investigate the average log-likelihood ratio (LLR) values and their distribution related to the erroneous bit-channels, and develop the Thresholded SC-Flip (TSCF) decoding algorithm. We also replace the LLR selection and sorting of SC-Flip with a comparator to reduce the implementation complexity. Simulation results demonstrate that for practical code lengths and a wide range of rates, TSCF shows negligible loss compared with the error-correction performance obtained when all single-errors are corrected. At matching maximum iterations, TSCF has an error-correction performance gain of up to 0.45 dB compared with SC-Flip decoding. At matching error-correction performance, the computational complexity of TSCF is reduced by up to 40% on average and requires up to <inline-formula> <tex-math notation="LaTeX">5\times </tex-math></inline-formula> lower maximum number of iterations.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2018.2873322