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This work identifies information-theoretic quantities that are closely related to the required list size for successive cancellation list (SCL) decoding to implement maximum-likelihood decoding. It also provides an approximation for these quantities that can be computed efficiently for very long codes. There is a concentration around the mean of the logarithm of the required list size for sufficiently large block lengths. We further provide a simple method to estimate the mean via density evolution for the binary erasure channel (BEC). Simulation results for the binary-input additive white Gaussian noise channel as well as the BEC demonstrate the accuracy of the mean estimate. A modified Reed-Muller code with dynamic frozen bits performs very close to the random coding union (RCU) bound down to the block error rate of $10^{-5}$ under SCL decoding with list size $L=128$ when the block length is $N=128$. The analysis shows how to modify the design to improve the performance when a more practical list size, e.g., $L=32$, is adopted while keeping the performance with $L=128$ unchanged. For the block length of $N=512$, a design performing within $0.4$ dB from the RCU bound down to the block error rate of $10^{-6}$ under an SCL decoder with list size $L=1024$ is provided. The design is modified using the new guidelines so that the performance improves with practical list sizes, e.g., $Lin{8,32,128}$, outperforming 5G designs.
This paper presents an efficient hardware design approach for list successive cancellation (LSC) decoding of polar codes. By applying path-overlapping scheme, the l instances of (l > 1) successive cancellation (SC) decoder for LSC with list size l ca
Polar codes are a class of channel capacity achieving codes that has been selected for the next generation of wireless communication standards. Successive-cancellation (SC) is the first proposed decoding algorithm, suffering from mediocre error-corre
A deep-learning-aided successive-cancellation list (DL-SCL) decoding algorithm for polar codes is introduced with deep-learning-aided successive-cancellation (DL-SC) decoding being a specific case of it. The DL-SCL decoder works by allowing additiona
Fast SC decoding overcomes the latency caused by the serial nature of the SC decoding by identifying new nodes in the upper levels of the SC decoding tree and implementing their fast parallel decoders. In this work, we first present a novel sequence
Polar codes are a class of linear block codes that provably achieves channel capacity, and have been selected as a coding scheme for $5^{rm th}$ generation wireless communication standards. Successive-cancellation (SC) decoding of polar codes has med