Polar Adaptive Successive Cancellation List Decoding Based on Segmentation Cyclic Redundancy Check
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摘要: 针对极化码连续取消列表(SCL)译码算法为获取较好性能而采用较多的保留路径数，导致译码复杂度较高的缺点，自适应SCL译码算法虽然在高信噪比下降低了一定的计算量，却带来了较高的译码延时。根据极化码的顺序译码结构，该文提出了一种分段循环冗余校验(CRC)与自适应选择保留路径数量相结合的SCL译码算法。仿真结果表明，与传统CRC辅助SCL译码算法、自适应SCL译码算法相比，该算法在码率R=0.5时，低信噪比下(–1 dB)复杂度降低了约21.6%，在高信噪比下(3 dB)复杂度降低了约64%，同时获得较好的译码性能。Abstract: Considering the problem that using a large number of reserved paths causes higher complexity in order to obtain better performance for polar code Successive Cancellation List (SCL) decoding, the adaptive SCL decoding algorithm at a high Signal to Noise Ratio (SNR) reduces a certain amount of calculations, however, brings a higher decoding delay. According to the order of polar code decoding, an SCL decoding algorithm combining segmentation Cyclic Redundancy Check (CRC) with adaptively selecting the number of reserved paths is proposed. The simulation results show that compared with the traditional CRC-assisted SCL decoding algorithm and adaptive-SCL algorithm, when the code rate is R=0.5, the complexity under low SNR (–1 dB) is reduced by about 21.6%, and the complexity at high SNR (3 dB) is reduced by about 64%, at the same time, better decoding performance is obtained.
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表 1 仿真参数
仿真参数 具体内容 编码结构 ${G_N} = {F^{ \otimes n}}$ 信道环境 AWGN 调制方式 BPSK 子信道置信序列构造法 DE-GA 译码算法 CA-SCL, AD-SCL, SCAD-SCL 
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表 2 R=0.5时不同算法复杂度比较
${E_b}/{N_0}$ (dB) –1.0 –0.5 0 0.5 1.0 1.5 2.0 2.5 3.0 AD-SCL 42304 42239 40850 32248 14153 4648 2034 1588 1536 SCAD-SCL 33177 33120 31918 24274 10590 2696 837 571 538
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