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Science China Information Sciences

A latency-reduced successive cancellation list decoder for polar codes

Yongrun Yu, Zhiwen Pan, Xiaosi Tan, Nan Liu, Xiaohu You, Fei Ding

Published Oct 15, 2018• 2 citations
Publisher
DOI
10.1007/s11432-018-9422-y

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The successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficult to apply the SCL decoding to the applications with limited processing time. To reduce the latency of the metric sorting, this paper proposes a new sorting method derived by analyzing path extension cases encountered in SCL decoding. The proposed method can avoid unnecessary sorting operations by adaptively determining the sorting size, and can be combined with other metric sorting methods. Simulation results show that the proposed method significantly reduces the decoding latency for various list sizes and code rates without degrading the error-correcting performance. The proposed method also becomes more effective as the code rate or the list size increases. Combined with the state-of-the-art sorting method, the proposed method reduces the average SCL decoding latency for a (1024, 512) polar code by 33.1% when the list size is 8.
Compared with the bit-wise successive cancellation list (SCL) decoding of polar codes, the node-based Fast SCL decoding significantly reduces the decoding latency by identifying special constituent codes and decoding these in parallel. To further reduce the latency of current Fast SCL decoders, we first propose a fast sequence repetition (SR) node-based SCL (Fast SR-SCL) decoding algorithm, which only involves one type of node in the SCL decoding tree. Furthermore, we employ the adaptive path splitting (APS) strategy to terminate the path splitting in the SR node early, without degrading the error-correcting performance. Numerical results show that for 5G uplink codes with a length of 1024 and rates of 1/4, 1/2, and 3/4, our decoder can deliver the same decoding performance while reducing the average latency by 34.5%, 38.0%, and 39.6% compared with the state-of-the-art Fast SCL decoder for a list size L = 8.
This work presents a fast successive-cancellation list flip (Fast-SCLF) decoding algorithm for polar codes that addresses the high latency issue associated with the successive-cancellation list flip (SCLF) decoding algorithm. We first propose a bit-flipping strategy tailored to the state-of-the-art fast successive-cancellation list (FSCL) decoding that avoids tree-traversal in the binary tree representation of SCLF, thus reducing the latency of the decoding process. We then derive a parameterized path selection error model to accurately estimate the bit index at which the correct decoding path is eliminated from the initial FSCL decoding. The trainable parameter is optimized online based on an efficient supervised learning framework. Simulation results show that for a polar code of length 512 with 256 information bits, with similar error-correction performance and memory consumption, the proposed Fast-SCLF decoder reduces up to 73.4% of the average decoding latency of the SCLF decoder with the same list size at the frame error rate of 10−4, while incurring a maximum computational complexity overhead of 27.6%. For the same polar code of length 512 with 256 information bits and at practical signal-to-noise ratios, the proposed decoder with list size 4 reduces 89.3% and 43.7% of the average complexity and decoding latency of the FSCL decoder with list size 32 (FSCL-32), respectively, while also reducing 83.2% of the memory consumption of FSCL-32. The significant improvements of the proposed decoder come at the cost of 0.07 dB error-correction performance degradation compared with FSCL-32.