Ahmad Bazzi

Ahmad Bazzi

he/him

Research Scientist

Deep Learning-Enabled Angle Estimation in Bistatic ISAC Systems

Published in 2023 IEEE Globecom Workshops (GC Wkshps), 2023

This invited paper presents a deep-learning architecture for joint angle-of-arrival and angle-of-departure estimation in bistatic integrated sensing and communication (ISAC) systems. The learned estimator approaches the performance of model-based methods at substantially lower computational complexity.

Recommended citation: S. Naoumi, A. Bazzi, R. Bomfin and M. Chafii, "Deep Learning-Enabled Angle Estimation in Bistatic ISAC Systems," in 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp. 854-859. (invited paper) https://ieeexplore.ieee.org/document/10464930

Show BibTeX
@article{naoumi2023deep,
  title   = {Deep Learning-Enabled Angle Estimation in Bistatic ISAC Systems},
  author  = {Salmane Naoumi and Ahmad Bazzi and Roberto Bomfin and Marwa Chafii},
  journal = {2023 IEEE Globecom Workshops (GC Wkshps)},
  pages   = {854--859},
  year    = {2023},
  month   = {dec},
  publisher = {IEEE},
  doi     = {10.1109/GCWkshps58843.2023.10464930},
  url     = {https://doi.org/10.1109/GCWkshps58843.2023.10464930},
}