The discovery of suitable automorphisms of polar codes gained a lot of attention by applying them in Automorphism Ensemble Decoding (AED) to improve the error-correction performance, especially for short block lengths. This paper introduces Successive Cancellation Automorphism List (SCAL) decoding of polar codes as a novel application of automorphisms in advanced Successive Cancellation List (SCL) decoding. Initialized with L permutations sampled from the automorphism group, a superposition of different noise realizations and path splitting takes place inside the decoder. In this way, the SCAL decoder automatically adapts to the channel conditions and outperforms the error-correction performance of conventional SCL decoding and AED. For a polar code of length 128, SCAL performs near Maximum Likelihood (ML) decoding with L=8, in contrast to M=16 needed decoder cores in AED. Application-Specific Integrated Circuit (ASIC) implementations in a 12 nm technology show that high-throughput, pipelined SCAL decoders outperform AED in terms of energy efficiency and power density, and SCL decoders additionally in area efficiency.

翻译：极化码中合适自同构的发现引起了广泛关注，通过将其应用于自同构集成译码（AED）来改善纠错性能，尤其是针对短码长。本文提出极化码的逐次消除自同构列表（SCAL）译码，作为自同构在先进逐次消除列表（SCL）译码中的一种新应用。利用从自同构组中采样的L个置换进行初始化，译码器内部会叠加不同的噪声实现与路径分裂。通过这种方式，SCAL译码器自动适应信道条件，在纠错性能上优于传统SCL译码和AED。对于长度为128的极化码，SCAL在L=8时接近最大似然（ML）译码性能，而AED需要M=16个译码核心。在12纳米工艺下实现的专用集成电路（ASIC）表明，高吞吐量的流水线SCAL译码器在能效和功率密度上优于AED，且在面积效率上额外优于SCL译码器。