On the Performance of Quantized Neural Networks based Digital Predistortion for PA linearization in OFDM systems-Reference-Cited by-同舟云学术

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On the Performance of Quantized Neural Networks based Digital Predistortion for PA linearization in OFDM systems

Published:2022-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
language:
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Author:

Falempin Alexis¹,Laurent Johan¹,Dore Jean-Baptiste¹,Zayani Rafik¹,Strinati Emilio Calvanese¹

Affiliation:

1. Leti, Univ. Grenoble Alpes,CEA,Grenoble,France,F-38000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10012685/10012692/10013013.pdf?arnumber=10013013

Reference14 articles.

1. Realistic power amplifier model for the New Radio evaluation;3GPP TSG-RAN WG 5 Tech Rep,2016

2. Adam: A method for stochastic optimization;kingma;3rd Int Con! on Learning Representations (ICLR),2015

3. Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation;bengio;CoRR,2013

4. Zynq UltraScale + RFSoC RF Data Converter v2.6 Gen 1/2/3;Tech Rep,2021

5. Zynq UltraScale XCZU9EG MPSoC Data Sheet;Tech Rep,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of Improved AHTVSSLMS Algorithm in Digital Predistortion System;2023 5th International Conference on Electronics and Communication, Network and Computer Technology (ECNCT);2023-08-18

2. Digital Predistortion of RF Power Amplifiers using DeepShift;2023 IEEE Wireless Communications and Networking Conference (WCNC);2023-03

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