Modified indirect learning applied to neural network-based pre-distortion of a concurrent dual-band CMOS power amplifier
Author:
Publisher
Springer Science and Business Media LLC
Subject
Surfaces, Coatings and Films,Hardware and Architecture,Signal Processing
Link
http://link.springer.com/content/pdf/10.1007/s10470-020-01741-7.pdf
Reference33 articles.
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2. Manyam, V. N., Pham, D. G., Jabbour, C., & Desgreys, P. (2018). A low-power high-performance digital predistorter for wideband power amplifiers. Analog Integrated Circuits and Signal Processing,. https://doi.org/10.1007/s10470-018-1263-9.
3. Naik, G., Liu, J., & Park, J. J. (2018). Coexistence of wireless technologies in the 5 GHz bands: A survey of existing solutions and a roadmap for future research. IEEE Communications Surveys Tutorials,. https://doi.org/10.1109/COMST.2018.2815585.
4. Dardaillon, M., Jabbour, C., & Srini, V. P. (2015). Adaptive digital pre-distortion for future wireless transmitters. In: 2015 IEEE international conference on electronics, circuits, and systems (ICECS). https://doi.org/10.1109/ICECS.2015.7440316
5. Kelly, N., Cao, W., & Zhu, A. (2017). Preparing linearity and efficiency for 5G: Digital predistortion for dual-band doherty power amplifiers with mixed-mode carrier aggregation. IEEE Microwave Magazine,. https://doi.org/10.1109/MMM.2016.2616185.
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