Decoding quadratic residue codes using deep neural networks

HIGHLIGHTS

  • who: Ming Wang et al. from the College of Computer Science, Chongqing University, Chongqing, China have published the research: Decoding Quadratic Residue Codes Using Deep Neural Networks, in the Journal: Electronics 2022, 11, 2717. of /2022/
  • what: In this paper a low-complexity decoder based on a neural network is proposed to decode binary quadratic residue (QR) codes.
  • future: The future work will include approaching ML performance for longer QR codes with less or the same complexity.

SUMMARY

    Binary channel codes are of significant importance in physical-layer digital . . .

     

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