In non-coherent bistatic MIMO ISAC, data-aided sensing yields a strict 3 dB effective SNR improvement at low SNR and faster performance scaling at high SNR versus pilot sensing, via closed-form random matrix theory asymptotics.
Sensing for free: Learn to localize more sources than antennas without pilots
2 Pith papers cite this work. Polarity classification is still indexing.
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An end-to-end neural transceiver jointly trained with 3D Gaussian Splatting loss enables sparse pilots and higher-fidelity large-scale 3D reconstructions from low-altitude aerial images.
citing papers explorer
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Fundamental Performance Limits of Non-Coherent ISAC: A Data-Aided Sensing Perspective
In non-coherent bistatic MIMO ISAC, data-aided sensing yields a strict 3 dB effective SNR improvement at low SNR and faster performance scaling at high SNR versus pilot sensing, via closed-form random matrix theory asymptotics.
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Efficient Transceiver Design for Aerial Image Transmission and Large-scale Scene Reconstruction
An end-to-end neural transceiver jointly trained with 3D Gaussian Splatting loss enables sparse pilots and higher-fidelity large-scale 3D reconstructions from low-altitude aerial images.