Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks

  title={Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks},
  author={Toshiki Matsumine and T. Koike-Akino and Ye Wang},
  journal={ICC 2019 - 2019 IEEE International Conference on Communications (ICC)},
  • Toshiki Matsumine, T. Koike-Akino, Ye Wang
  • Published 2019
  • Computer Science, Engineering, Mathematics
  • ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
This paper studies a new application of deep learning (DL) for optimizing constellations in two-way relaying with physical-layer network coding (PNC), where deep neural network (DNN)-based modulation and demodulation are employed at each terminal and relay node. We train DNNs such that the cross entropy loss is directly minimized, and thus it maximizes the likelihood, rather than considering the Euclidean distance of the constellations. The proposed scheme can be extended to higher level… Expand
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