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Software demodulation of weak radio signals using convolutional neural network

26 February 2025
Mykola Kozlenko
Ihor Lazarovych
Valerii Tkachuk
Vira Vialkova
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Abstract

In this paper we proposed the use of JT65A radio communication protocol for data exchange in wide-area monitoring systems in electric power systems. We investigated the software demodulation of the multiple frequency shift keying weak signals transmitted with JT65A communication protocol using deep convolutional neural network. We presented the demodulation performance in form of symbol and bit error rates. We focused on the interference immunity of the protocol over an additive white Gaussian noise with average signal-to-noise ratios in the range from -30 dB to 0 dB, which was obtained for the first time. We proved that the interference immunity is about 1.5 dB less than the theoretical limit of non-coherent demodulation of orthogonal MFSK signals.

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@article{kozlenko2025_2502.19097,
  title={ Software demodulation of weak radio signals using convolutional neural network },
  author={ Mykola Kozlenko and Ihor Lazarovych and Valerii Tkachuk and Vira Vialkova },
  journal={arXiv preprint arXiv:2502.19097},
  year={ 2025 }
}
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