mlsanityData to 14 Oct 2026

Software demodulation of weak radio signals using convolutional neural network

arXiv 2502.19097 ↗First posted 26 Feb 2025cs.LG eess.SPcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 26 Feb 2025.

Builds on

2 of 15 references.

References · 2

  1. 2017An Introduction to Deep Learning for the Physical Layercited by 233
  2. 2025Software defined demodulation of multiple frequency shift keying with dense neural network for weak signal communicationscited by 5

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Citing papers per year: 2025: 4.

4 papers.

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  3. 2025Supervised machine learning based signal demodulation in chaotic communicationscited by 0
  4. 2025Research on a hybrid LSTM-CNN-Attention model for text-based web content classificationcited by 0