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.
Orthogonal time frequency space modula- tion
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
DBU-OFDM uses recursive Householder reflections to parameterize a block-unitary transform on data subcarriers, yielding lower PAPR, better frequency-selective fading performance, and improved range-velocity estimation in integrated sensing and communication while retaining comb pilots and hardware-1
The MCC pilot pattern, derived from a mixed-integer optimization balancing grid coverage and collinearity suppression, improves surrogate geometry metrics and latest-slot recovery performance in TDD systems.
citing papers explorer
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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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DBU-OFDM: A Trainable Deep Block-Unitary OFDM Waveform for Integrated Sensing and Communication
DBU-OFDM uses recursive Householder reflections to parameterize a block-unitary transform on data subcarriers, yielding lower PAPR, better frequency-selective fading performance, and improved range-velocity estimation in integrated sensing and communication while retaining comb pilots and hardware-1
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Covering-radius and Collinearity- Minimizing Pilots for Channel Estimation in TDD Systems
The MCC pilot pattern, derived from a mixed-integer optimization balancing grid coverage and collinearity suppression, improves surrogate geometry metrics and latest-slot recovery performance in TDD systems.