For polar codes, successive cancellation list (SCL) decoding algorithm significantly improves finite-length performance compared to SC decoding. SCL-flip decoding can further enhance the performance but the gain diminishes as code length increases, due to the difficulty in locating the first error bit position. In this work, we introduce an SCL-perturbation decoding algorithm to address this issue. A basic version of the algorithm introduces small random perturbations to the received symbols before each SCL decoding attempt, and exhibits non-diminishing gain at large block lengths. Its enhanced version adaptively performs random perturbations or directional perturbation on each received symbol according to previous decoding results, and managed to correct more errors with fewer decoding attempts. Extensive simulation results demonstrate stable gains across various code rates, lengths and list sizes. To the best of our knowledge, this is the first SCL enhancement with non-diminishing gains as code length increases, and achieves unprecedented efficiency. With only one additional SCL-$L$ decoding attempt (in total two), the proposed algorithm achieves SCL-$2L$-equivalent performance. Since the gain is obtained without increasing list size, the algorithm is best suited for hardware implementation.

翻译：对于极化码，连续消除列表（SCL）译码算法相比SC译码显著改善了有限码长性能。SCL翻转译码能进一步提升性能，但随着码长增加，由于难以定位首个错误比特位置，性能增益逐渐减弱。本文提出一种SCL扰动译码算法以解决该问题。该算法的基本版本在每次SCL译码尝试前对接收符号引入微小随机扰动，并在大码长下展现出非递减的增益。其增强版本根据先前的译码结果，自适应地对每个接收符号执行随机扰动或定向扰动，从而以更少的译码尝试纠正更多错误。大量仿真结果表明，该算法在不同码率、码长和列表大小下均能获得稳定的性能增益。据我们所知，这是首个随码长增加具有非递减增益的SCL增强算法，并实现了前所未有的效率。仅需一次额外的SCL-$L$译码尝试（总计两次），所提算法即可达到SCL-$2L$等效性能。由于该增益无需增大列表大小即可获得，该算法尤其适用于硬件实现。