A sparsity-agnostic DD channel estimator exploits Cartesian-product support structure and BIC-based dimension selection to recover exact support with high probability and achieve near-oracle reconstruction accuracy.
Affine frequency division multiplexing for next generation wireless communications
3 Pith papers cite this work. Polarity classification is still indexing.
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Under a dynamic generalized channel model, OFDM and DFT-s-OFDM can be tuned for superior reliability and stability compared to AFDM and OTFS, which only retain advantages in sparse stationary settings.
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
citing papers explorer
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Delay-Doppler Domain Channel Estimation: What if Sparsity is Unknown?
A sparsity-agnostic DD channel estimator exploits Cartesian-product support structure and BIC-based dimension selection to recover exact support with high probability and achieve near-oracle reconstruction accuracy.
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Channel-Aware Waveform Selection Criteria Across Different Waveform Domains
Under a dynamic generalized channel model, OFDM and DFT-s-OFDM can be tuned for superior reliability and stability compared to AFDM and OTFS, which only retain advantages in sparse stationary settings.
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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