Study On Optical Communications, Volume. 48, Issue 4, 17(2022)

Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes

Xue-lu DENG and Da-qin PENG*
Author Affiliations
  • School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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    Figures & Tables(8)
    [in Chinese]
    [in Chinese]
    [in Chinese]
    [in Chinese]
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    • Table 1. [in Chinese]

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      Table 1. [in Chinese]

      参数选项
      测试平台TensorFlow
      调制方式BPSK
      SNR范围/dB1~5
      训练集大小7.5×104
      测试集大小3×103
      优化算法AdaGrad
      损失函交叉熵
      数学习率0.001
      Epochs25
    • Table 2. [in Chinese]

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      Table 2. [in Chinese]

      算法乘法运算加法运算存储空间
      BP02TBPNlog2N~30720(100%)0
      DNN-BP2TNlog2N(100%)2TNlog2N~3840(12.5%)2TNlog2N~3840(100%)
      RNN-OMS-BP04TNlog2N~7680(25%)2N(log2N +1)~896(23.3%)
      RNN-OMS-BP-L03TNlog2N~5760(18.75%)2N(log2N+1)-N/8~888(23.1%)
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    Xue-lu DENG, Da-qin PENG. Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes[J]. Study On Optical Communications, 2022, 48(4): 17

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    Paper Information

    Category: Research Articles

    Received: Dec. 1, 2021

    Accepted: --

    Published Online: Aug. 5, 2022

    The Author Email: Da-qin PENG (pengdq@cqupt.edu.cn)

    DOI:10.13756/j.gtxyj.2022.04.004

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