We propose a belief propagation list (BPL) decoder with comparable
performance to the successive cancellation list (SCL) decoder of polar codes,
which already achieves the maximum likelihood (ML) bound of polar codes for
sufficiently large list size $L$. The proposed decoder is composed of multiple
parallel independent belief propagation (BP) decoders based on differently
permuted polar code factor graphs. A list of possible transmitted codewords is
generated and the one closest to the received vector, in terms of Euclidean
distance, is picked. To the best of our knowledge, the proposed BPL decoder
provides the best performance of plain polar codes under iterative decoding
known so far. The proposed algorithm does not require any changes in the polar
code structure itself, rendering the BPL into an alternative to the SCL
decoder, equipped with a soft output capability enabling, e.g., iterative
detection and decoding to further improve performance. Further benefits are
lower decoding latency compared to the SCL decoder and the possibility of high
throughput implementations. Additionally, we show that a different selection
strategy of frozen bit positions can further enhance the error-rate performance
of the proposed decoder.

本文提出了一种基于置信传播列表（BPL）的解码器，实现了与连续取消列表（SCL）解码器相当的性能，并且没有改变极化码的结构，是连续取消列表（SCL）解码器的一种替代方案，可用于迭代检测和译码以进一步提高性能。此外，该算法具有较低的解码延迟和高吞吐量实现的可能性，并且可以通过不同的选位冻结策略进一步增强误码率性能。

极化码的置信传播列表译码

Belief Propagation List Decoding of Polar Codes

In this work, we show that polar belief propagation (BP) decoding exhibits an
error floor behavior which is caused by clipping of the log-likelihood ratios
(LLR). The error floor becomes more pronounced for clipping to smaller
LLR-values. We introduce a single-value measure quantifying a "relative error
floor", showing, by exhaustive simulations for different lengths, that the
error floor is mainly caused by inadequate clipping values. We propose four
modifications to the conventional BP decoding algorithm to mitigate this error
floor behavior, demonstrating that the error floor is a decoder property, and
not a code property. The results agree with the fact that polar codes are
theoretically proven to not suffer from error floors. Finally, we show that
another cause of error floors can be an improper selection of frozen bit
positions.

本文研究发现极化置信传播解码存在错误地板效应，是由对数似然比剪切引起的，并提出了四项算法改进策略来缓解该问题，实验证明错误地板是解码器的属性而不是编码器的属性，同时还发现错误地板的另一个原因是冻结比特位置的选择不当。