Spectral-Efficient End-to-End Beamforming for 6G XL-MIMO: Synergizing Channel Sensing and Spatial-Frequency Sparsity with Deep Learning.

Wen Y, Zeng X, Xie X

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DOI: 10.3390/s26072012
Published: 2026 Mar 24
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s26072012,
  title = {Spectral-Efficient End-to-End Beamforming for 6G XL-MIMO: Synergizing Channel Sensing and Spatial-Frequency Sparsity with Deep Learning.},
  author = {Wen Y and Zeng X and Xie X},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26072012},
  url = {https://doi.org/10.3390/s26072012}
}

RIS

TY  - JOUR
TI  - Spectral-Efficient End-to-End Beamforming for 6G XL-MIMO: Synergizing Channel Sensing and Spatial-Frequency Sparsity with Deep Learning.
AU  - Wen Y
AU  - Zeng X
AU  - Xie X
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26072012
UR  - https://doi.org/10.3390/s26072012
ER  -

APA

Y, W., X, Z., & X, X. (2026). Spectral-Efficient End-to-End Beamforming for 6G XL-MIMO: Synergizing Channel Sensing and Spatial-Frequency Sparsity with Deep Learning.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26072012

Source records

pubmed · retrieved 2026-11-10T05:54:34.005Z
europe-pmc · retrieved 2026-11-10T05:54:34.018Z
doaj · retrieved 2026-11-10T05:54:34.029Z