Deep learning approach for hybrid beamforming design in MU-MISO mmWave systems.

Ghaith E, Mekkawy T, Abouelfadl AA, Mahran A

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DOI: 10.1038/s41598-026-35247-5
Published: 2026 Feb 4
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-35247-5,
  title = {Deep learning approach for hybrid beamforming design in MU-MISO mmWave systems.},
  author = {Ghaith E and Mekkawy T and Abouelfadl AA and Mahran A},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-35247-5},
  url = {https://doi.org/10.1038/s41598-026-35247-5}
}

RIS

TY  - JOUR
TI  - Deep learning approach for hybrid beamforming design in MU-MISO mmWave systems.
AU  - Ghaith E
AU  - Mekkawy T
AU  - Abouelfadl AA
AU  - Mahran A
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-35247-5
UR  - https://doi.org/10.1038/s41598-026-35247-5
ER  -

APA

E, G., T, M., AA, A., & A, M. (2026). Deep learning approach for hybrid beamforming design in MU-MISO mmWave systems.. Scientific reports. https://doi.org/10.1038/s41598-026-35247-5

Source records

pubmed · retrieved 2026-09-25T11:58:06.587Z
europe-pmc · retrieved 2026-09-25T11:58:06.596Z
doaj · retrieved 2026-09-25T11:58:06.580Z