Benchmarking and Interpreting End-to-End Learning of MIMO and Multi-User Communication

Author:

Song Jinxiang1ORCID,Hager Christian1ORCID,Schroder Jochen2ORCID,O'Shea Timothy J.3ORCID,Agrell Erik1ORCID,Wymeersch Henk1ORCID

Affiliation:

1. Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

2. Department of Microtechnology and Nanoscience, Chalmers University of Technology, Gothenburg, Sweden

3. Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA

Funder

Knut and Alice Wallenberg Foundation

Swedish Research Council

European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Cited by 7 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. Decode-and-Forward Based Cooperative MIMO System using Deep Learning for Wireless Body Area Networks;2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS);2023-11-27

2. Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift system;Nano Communication Networks;2023-09

3. Deep learning based MIMO systems using open-loop autoencoder;AEU - International Journal of Electronics and Communications;2023-08

4. Bit Error and Block Error Rate Training for ML-Assisted Communication;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

5. Vision Transformer for Adaptive Image Transmission over MIMO Channels;ICC 2023 - IEEE International Conference on Communications;2023-05-28

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