High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods

This work develops high-resolution joint-estimation methods for communication-centric integrated sensing and communication (ISAC). It combines a deep-learning solution with a parametric estimator, both targeting super-resolution accuracy in angle and delay estimation while preserving the underlying communication waveform’s performance.

Recommended citation: A. Bazzi, S. Naoumi, R. Bomfin and M. Chafii, "High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods," in IEEE Journal on Selected Areas in Communications, vol. 44, 2025. https://doi.org/10.1109/JSAC.2025.3639350

@article{bazzi2025high-resolution,
  title   = {High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods},
  author  = {Ahmad Bazzi and Salmane Naoumi and Roberto Bomfin and Marwa Chafii},
  journal = {IEEE Journal on Selected Areas in Communications},
  volume  = {44},
  year    = {2025},
  month   = {dec},
  publisher = {IEEE},
  doi     = {10.1109/JSAC.2025.3639350},
  url     = {https://doi.org/10.1109/JSAC.2025.3639350},
}