On the performance of quantized neural networks based digital predistortion for PA linearization in OFDM systems
- DOI
- 10.1109/vtc2022-fall57202.2022.10013013
- Published
- 2022
- Container
- Not recorded
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/vtc2022-fall57202.2022.10013013,
title = {On the performance of quantized neural networks based digital predistortion for PA linearization in OFDM systems},
author = {Alexis Falempin and Johan Laurent and Jean-Baptiste Dore and Rafik Zayani and Emilio Calvanese Strinati},
year = {2022},
doi = {10.1109/vtc2022-fall57202.2022.10013013},
url = {https://doi.org/10.1109/vtc2022-fall57202.2022.10013013}
}RIS
TY - JOUR TI - On the performance of quantized neural networks based digital predistortion for PA linearization in OFDM systems AU - Alexis Falempin AU - Johan Laurent AU - Jean-Baptiste Dore AU - Rafik Zayani AU - Emilio Calvanese Strinati PY - 2022 DO - 10.1109/vtc2022-fall57202.2022.10013013 UR - https://doi.org/10.1109/vtc2022-fall57202.2022.10013013 ER -
APA
Falempin, A., Laurent, J., Dore, J., Zayani, R., & Strinati, E. C. (2022). On the performance of quantized neural networks based digital predistortion for PA linearization in OFDM systems. https://doi.org/10.1109/vtc2022-fall57202.2022.10013013
Source records
- hal · retrieved 2026-09-26T11:08:32.387Z