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Recursive Processing Algorithm for Low Complexity Decoding of Polar Codes With Large Kernels
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DOI：10.1109/TCOMM.2023.3285773.png)
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Abstract
En 中文
A reduced complexity algorithm is presented for computing the log-likelihood ratios (LLRs) arising in the successive cancellation (SC) decoder for polar codes with large kernels of arbitrary dimension. The proposed algorithm exploits a recursive trellis representation of the codes generated by submatrices of the polarization kernel and enables polar codes based on large kernels to be decoded with lower complexity compared to the codes based on the Arikan kernel with the same performance. Extensions to the case of non-binary kernels are presented.
Keywords:
Kernel
Polar codes
Codes
Complexity theory
Maximum likelihood decoding
Viterbi algorithm
Symbols
large kernels
recursive maximum likelihood decoding
non-binary codes
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W