Phase-Normalized Neural Network for Linearization of RF Power Amplifiers
Author:
Affiliation:
1. Nokia Bell Labs, Antwerp, Belgium
2. Department of Electrical Engineering, Tampere University, Tampere, Finland
Funder
European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie
Academy of Finland
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9944983/10239679/10176354.pdf?arnumber=10176354
Reference24 articles.
1. Virtual DPD Neural Network Predistortion for OFDM-based MU-Massive MIMO
2. Iterative Learning Control for RF Power Amplifier Linearization
3. Review of the Neural Network based Digital Predistortion Linearization of Multi-Band/MIMO Transmitters
4. Non-Linear Digital Self-Interference Cancellation for In-Band Full-Duplex Radios Using Neural Networks
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1. Recursive Neural Network With Phase-Normalization for Modeling and Linearization of RF Power Amplifiers;IEEE Microwave and Wireless Technology Letters;2024-06
2. Walsh-domain Neural Network for Power Amplifier Behavioral Modelling and Digital Predistortion;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19
3. GPU versus FPGA implementation of a digital predistortion linearizer for wideband radiofrequency power amplifiers;AEU - International Journal of Electronics and Communications;2024-01
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