Successive cancellation (SC) is the first and widely known decoder of polar codes, which has received a lot of attentions. However, its decoding schedule generating methods are still primitive. Based on a newly found factor, this study proposes an online method to generate the decoding schedule of SC decoder by a non‐recursive way. The decoding schedule of SC decoder includes two parts. One is to determine which of likelihood ratios (LRs) can be shared and which of LRs need to be calculated. The other is to select a calculation formula for a LR to be computed. As shown by the comparisons among the proposed method and existing methods, the proposed method solves the first part of the decoding schedule with constant critical path delay and lower space complexity, and solves the second part of the decoding schedule with less calculations. Besides, experimental results show that the proposed method does not affect the error performance of polar codes.
Neural Network Decoders (NNDs) have been recently considered and investigated as an alternative to the classical algorithms for decoding Polar Codes. In particular, a class of partitioned decoders has been proposed where modified Successive Cancellation (SC) or Belief Propagation (BP) algorithms exploit the neural network decoding of short sublocks. Although NNDs work as one-shot decoders with small decoding latency, the performance of these decoders, in comparison with classic approaches, still suffers from some losses; this fact limits their application to codes with short/medium length. In this article we introduce the novel Neural Successive Cancellation List (NSCL) decoder, as a partitioned version of the SC decoder operating on a list of L multiple decoding candidates that are built with the decoded sub-blocks obtained from a set of NNDs working in parallel at each partition. This decoder significantly improves the BER performance of the non-list version under the same code length. Hence, it reduces the intrinsic loss of performance given by the use of NNDs and allows the application of NN-based decoding to longer codewords.
In this paper, two decoding algorithms based on Successive-Cancellation (SC) are proposed to improve the error-correction performance of cyclic redundancy check (CRC)-aided polar codes while aiming for a low-complexity implementation. Comparisons with Dynamic SC Flip (DSCF) and SC Perturbation (SCP) are carried out since the proposed DSCF and Perturbation (DSCFP) and Perturbed DSCF (PDSCF) algorithms combine both methods. The analysis includes comparisons with several code lengths
Nand various number of decoding attempts
Tmax. For
N=1024and the coding rate
R=1/2, the DSCF and the SCP algorithms with
Tmax=17are bested by approximately 0.1 dB at block-error rate (BLER) of 0.001. At BLER = 10−6and for
Tmax=64, the gain is of 0.375 dB and > 0.5 dB with respect to DSCF and SCP, respectively. At high signal-to-noise ratio, the average computational complexity of the proposed algorithms is virtually equivalent to that of SC.