A CNN modulator jointly trained with a neural receiver spreads information across local time-frequency neighborhoods in OFDM, breaking QAM rotational symmetry to support sparse or zero pilots under high Doppler.
Advances in the neural network quantization: A comprehensive review,
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A review of CubeSat intrusion detection challenges identifies gaps in current methods and positions TinyML as a resource-efficient solution while outlining future research directions.
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Deep-OFDM: Neural Modulation for High Mobility
A CNN modulator jointly trained with a neural receiver spreads information across local time-frequency neighborhoods in OFDM, breaking QAM rotational symmetry to support sparse or zero pilots under high Doppler.
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Towards Resilient Intrusion Detection in CubeSats: Challenges, TinyML Solutions, and Future Directions
A review of CubeSat intrusion detection challenges identifies gaps in current methods and positions TinyML as a resource-efficient solution while outlining future research directions.