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Sequential Decoding of Short Length Binary Codes: Performance Versus Complexity
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DOI：10.1109/LCOMM.2021.3095895.png)
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摘要
En 中文
Sequential decoding of short length binary codes for the additive white Gaussian noise channel is considered. A variant of the variable-bias term (VBT) metric is introduced, producing useful trade-offs between performance and computational complexity. Comparisons are made with tail-biting convolutional codes decoded with a wrap-around Viterbi algorithm (WAVA) and with polar codes under successive-cancellation list (SCL) decoding. It is found that sequential decoding with the improved VBT metric has a better performance-complexity tradeoff than tail-biting codes under WAVA decoding (except at low complexities) but a worse performance-complexity tradeoff than polar codes under SCL decoding (except at high complexities).
Keyword:
Decoding
Measurement
Complexity theory
Signal to noise ratio
Maximum likelihood decoding
Polar codes
Convolutional codes
Decoding complexity
short length codes
sequential decoding
stack algorithm
variable bias-term metric
polar codes