Machine Learning Based End-to-End Constellation Training for Communication Systems
Author:
Affiliation:
1. Yuan Ze University,Department of Electrical Engineering,Taoyuan,Taiwan, R.O.C.
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9979726/9979808/09980231.pdf?arnumber=9980231
Reference15 articles.
1. An Autoencoder-Based Solution for IQ Constellation Analysis
2. Geometric Constellation Shaping Using Initialized Autoencoders
3. Meta-Modeling for Autoencoder-Based End-to-End Communications Systems
4. On Correctness of Automatic Differentiation for Non-Differentiable Functions;lee;Proceedings of the 34th International Conference on Neural Information Processing Systems ser NIPS'20,0
5. Sionna: An Open-Source Library for Next-Generation Physical Layer Research;hoydis;ArXiv Preprint,2022
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1. An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning;ICC 2024 - IEEE International Conference on Communications;2024-06-09
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