Deep Reinforcement Learning-Based Energy-Efficient Resource Allocation and Scheduling in 6G-Enabled UAV-Assisted IoT Wireless Networks
- DOI
- 10.3390/s26175483
- Published
- 2026-08-29
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s26175483,
title = {Deep Reinforcement Learning-Based Energy-Efficient Resource Allocation and Scheduling in 6G-Enabled UAV-Assisted IoT Wireless Networks},
author = {Ali Nauman and Sung Won Kim},
year = {2026},
journal = {Sensors},
doi = {10.3390/s26175483},
url = {https://doi.org/10.3390/s26175483}
}RIS
TY - JOUR TI - Deep Reinforcement Learning-Based Energy-Efficient Resource Allocation and Scheduling in 6G-Enabled UAV-Assisted IoT Wireless Networks AU - Ali Nauman AU - Sung Won Kim PY - 2026 JO - Sensors DO - 10.3390/s26175483 UR - https://doi.org/10.3390/s26175483 ER -
APA
Nauman, A., & Kim, S. W. (2026). Deep Reinforcement Learning-Based Energy-Efficient Resource Allocation and Scheduling in 6G-Enabled UAV-Assisted IoT Wireless Networks. Sensors. https://doi.org/10.3390/s26175483
Source records
- crossref · retrieved 2026-09-24T17:17:50.897Z