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Sebastian Dörner
Sebastian Dörner
在 inue.uni-stuttgart.de 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Deep learning based communication over the air
S Dörner, S Cammerer, J Hoydis, S Ten Brink
IEEE Journal of Selected Topics in Signal Processing 12 (1), 132-143, 2017
8812017
OFDM-autoencoder for end-to-end learning of communications systems
A Felix, S Cammerer, S Dörner, J Hoydis, S Ten Brink
2018 IEEE 19th International Workshop on Signal Processing Advances in …, 2018
2962018
Trainable communication systems: Concepts and prototype
S Cammerer, FA Aoudia, S Dörner, M Stark, J Hoydis, S Ten Brink
IEEE Transactions on Communications 68 (9), 5489-5503, 2020
1632020
On deep learning-based massive MIMO indoor user localization
M Arnold, S Dorner, S Cammerer, S Ten Brink
2018 IEEE 19th International Workshop on Signal Processing Advances in …, 2018
592018
Enabling FDD massive MIMO through deep learning-based channel prediction
M Arnold, S Dörner, S Cammerer, S Yan, J Hoydis, S Brink
arXiv preprint arXiv:1901.03664, 2019
572019
Online label recovery for deep learning-based communication through error correcting codes
S Schibisch, S Cammerer, S Dörner, J Hoydis, S ten Brink
2018 15th International Symposium on Wireless Communication Systems (ISWCS), 1-5, 2018
332018
Towards practical indoor positioning based on massive mimo systems
M Widmaier, M Arnold, S Dorner, S Cammerer, S ten Brink
2019 IEEE 90th vehicular technology conference (VTC2019-Fall), 1-6, 2019
302019
WGAN-based Autoencoder Training Over-the-air
S Dörner, M Henninger, S Cammerer, S ten Brink
2020 IEEE 21st International Workshop on Signal Processing Advances in …, 2020
282020
On recurrent neural networks for sequence-based processing in communications
D Tandler, S Dörner, S Cammerer, S ten Brink
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 537-543, 2019
282019
Deep-learning autoencoder for coherent and nonlinear optical communication
T Uhlemann, S Cammerer, A Span, S Dörner, S ten Brink
Photonic Networks; 21th ITG-Symposium, 1-8, 2020
252020
Towards practical FDD massive MIMO: CSI extrapolation driven by deep learning and actual channel measurements
M Arnold, S Dörner, S Cammerer, J Hoydis, S ten Brink
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1972-1976, 2019
232019
A distributed massive MIMO channel sounder for “big CSI data”-driven machine learning
F Euchner, M Gauger, S Dörner, S ten Brink
WSA 2021; 25th International ITG Workshop on Smart Antennas, 1-6, 2021
192021
S. t. Brink,“Enabling FDD massive MIMO through deep learning-based channel prediction,”
M Arnold, S Dörner, S Cammerer, S Yan, J Hoydis
arXiv preprint arXiv:1901.03664, 2019
152019
Learning joint detection, equalization and decoding for short-packet communications
S Dörner, J Clausius, S Cammerer, S ten Brink
IEEE Transactions on Communications 71 (2), 837-850, 2022
122022
Serial vs. parallel turbo-autoencoders and accelerated training for learned channel codes
J Clausius, S Dörner, S Cammerer, S ten Brink
2021 11th International Symposium on Topics in Coding (ISTC), 1-5, 2021
112021
Improving triplet-based channel charting on distributed massive MIMO measurements
F Euchner, P Stephan, M Gauger, S Dörner, S Ten Brink
2022 IEEE 23rd International Workshop on Signal Processing Advances in …, 2022
92022
Adaptive neural network-based OFDM receivers
MB Fischer, S Dörner, S Cammerer, T Shimizu, H Lu, S Ten Brink
2022 IEEE 23rd International Workshop on Signal Processing Advances in …, 2022
72022
Efficient FPGA implementation of an ANN-based demapper using cross-layer analysis
J Ney, B Hammoud, S Dörner, M Herrmann, J Clausius, S Ten Brink, ...
Electronics 11 (7), 1138, 2022
62022
End-to-end learning for physical layer communications
S Cammerer, S Dörner, J Hoydis, S ten Brink
International Zurich Seminar on Information and Communication (IZS 2018 …, 2018
62018
Wiener filter versus recurrent neural network-based 2d-channel estimation for V2X communications
MB Fischer, S Dörner, S Cammerer, T Shimizu, B Cheng, H Lu, ...
2021 IEEE Intelligent Vehicles Symposium (IV), 458-465, 2021
52021
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