• Corpus ID: 239024894

Wideband and Entropy-Aware Deep Soft Bit Quantization

@article{Arvinte2021WidebandAE,
  title={Wideband and Entropy-Aware Deep Soft Bit Quantization},
  author={Marius Arvinte and Jonathan I. Tamir},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.09541}
}
Deep learning has been recently applied to physical layer processing in digital communication systems in order to improve end-to-end performance. In this work, we introduce a novel deep learning solution for soft bit quantization across wideband channels. Our method is trained end-to-end with quantizationand entropy-aware augmentations to the loss function and is used at inference in conjunction with source coding to achieve near-optimal compression gains over wideband channels. To efficiently… 

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