Deep Learning-Enabled Angle Estimation in Bistatic ISAC Systems

Salmane Naoumi, Ahmad Bazzi, Roberto Bomfin, Marwa Chafii

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Integrated sensing and communication (ISAC) is becoming a vital technology for future wireless systems and is particularly relevant for many applications requiring both high-performance sensing and wireless communications. Our work presents a novel algorithm based on deep learning for estimating angles of arrival and angles of departure in bistatic ISAC systems, exploiting orthogonal frequency division multiplexing signals initially designed for communication purposes. Our proposed method incorporates a complex-valued neural network that takes advantage of the estimated channel matrix, along with a preprocessing step for coarse timing estimation. Comparative analysis with an adapted version of the multiple signal classification method demonstrates the effectiveness of our approach, showcasing remarkable performance in terms of mean squared error while requiring lower computational complexity.

Original languageEnglish (US)
Title of host publication2023 IEEE Globecom Workshops, GC Wkshps 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9798350370218
StatePublished - 2023
Event2023 IEEE Globecom Workshops, GC Wkshps 2023 - Kuala Lumpur, Malaysia
Duration: Dec 4 2023Dec 8 2023

Publication series

Name2023 IEEE Globecom Workshops, GC Wkshps 2023


Conference2023 IEEE Globecom Workshops, GC Wkshps 2023
CityKuala Lumpur


  • angle of arrival (AoA) esti-mation
  • angle of departure (AoD) estimation
  • bistatic radar
  • deep learning (DL)
  • Integrated sensing and communication (ISAC)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication


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