路径度量辅助的极化码比特翻转译码算法与结构
Algorithm and Architecture for Path Metric Aided Bit-Flipping Decoding of Polar Codes
摘要：
极化码由于其容量可达性，近年来受到越来越多研究者的关注。然而，在连续消除（SC）解码下，它们的纠错性能在短或中等块长度下劣于其他现代信道码。SC翻转（SCF）解码算法通过识别初始SC解码中可能的错误判决并在后续解码尝试中翻转它们，显示出比SC解码更高的性能。然而，当码字中存在多于一个错误判决时，它的性能不佳。在本文中，我们提出了一个路径度量辅助的比特翻转解码算法，以识别和纠正更多的错误有效。在该算法中，基于基于对数似然比（LLR）的路径度量和比特翻转度量来生成比特翻转列表。路径度量用于验证比特翻转的有效性。为了降低解码延迟和计算复杂度，设计了相应的流水线结构。在误帧率为$10^{-4}$的情况下，采用这些译码算法和流水线结构，与SCF译码相比，纠错性能提高了0.25 dB，且平均译码时延较低。
英文摘要：
Polar codes attract more and more attention of researchers in recent years, since its capacity achieving property. However, their error-correction performance under successive cancellation (SC) decoding is inferior to other modern channel codes at short or moderate blocklengths. SC-Flip (SCF) decoding algorithm shows higher performance than SC decoding by identifying possibly erroneous decisions made in initial SC decoding and flipping them in the sequential decoding attempts. However, it performs not well when there are more than one erroneous decisions in a codeword. In this paper, we propose a path metric aided bit-flipping decoding algorithm to identify and correct more errors efficiently. In this algorithm, the bit-flipping list is generated based on both log likelihood ratio (LLR) based path metric and bit-flipping metric. The path metric is used to verify the effectiveness of bit-flipping. In order to reduce the decoding latency and computational complexity, its corresponding pipeline architecture is designed. By applying these decoding algorithms and pipeline architecture, an improvement on error-correction performance can be got up to 0.25dB compared with SCF decoding at the frame error rate of $10^{-4}$, with low average decoding latency.
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