Christian Häger
Christian Häger
Assistant Professor, Chalmers University of Technolgy, Department of Electrical Engineering
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Citata da
Citata da
Nonlinear interference mitigation via deep neural networks
C Häger, HD Pfister
Optical fiber communication conference, W3A. 4, 2018
Physics-based deep learning for fiber-optic communication systems
C Häger, HD Pfister
IEEE Journal on Selected Areas in Communications 39 (1), 280-294, 2020
Achievable information rates for nonlinear fiber communication via end-to-end autoencoder learning
S Li, C Häger, N Garcia, H Wymeersch
2018 European Conference on Optical Communication (ECOC), 1-3, 2018
Pruning and quantizing neural belief propagation decoders
A Buchberger, C Häger, HD Pfister, L Schmalen, AG i Amat
IEEE Journal on Selected Areas in Communications 39 (7), 1957-1966, 2020
Design of APSK constellations for coherent optical channels with nonlinear phase noise
C Häger, A Graell i Amat, A Alvarado, E Agrell
IEEE Trans. Commun. 61 (8), 3362-3373, 2013
Approaching miscorrection-free performance of product codes with anchor decoding
C Häger, HD Pfister
IEEE Transactions on Communications 66 (7), 2797-2808, 2018
End-to-end learning of geometrical shaping maximizing generalized mutual information
K Gümüş, A Alvarado, B Chen, C Häger, E Agrell
2020 Optical Fiber Communications Conference and Exhibition (OFC), 1-3, 2020
Learned belief-propagation decoding with simple scaling and SNR adaptation
M Lian, F Carpi, C Häger, HD Pfister
2019 IEEE International Symposium on Information Theory (ISIT), 161-165, 2019
Deep learning of the nonlinear Schrödinger equation in fiber-optic communications
C Häger, HD Pfister
2018 IEEE International Symposium on Information Theory (ISIT), 1590-1594, 2018
Reinforcement learning for channel coding: Learned bit-flipping decoding
F Carpi, C Häger, M Martalò, R Raheli, HD Pfister
2019 57th Annual Allerton Conference on Communication, Control, and …, 2019
Revisiting efficient multi-step nonlinearity compensation with machine learning: An experimental demonstration
V Oliari, S Goossens, C Häger, G Liga, RM Bütler, M van den Hout, ...
Journal of Lightwave Technology 38 (12), 3114-3124, 2020
Density Evolution for Deterministic Generalized Product Codes on the Binary Erasure Channel at High Rates
C Häger, HD Pfister, A Graell i Amat, F Brännström
IEEE Trans. Inf. Theory 63 (7), 4357-4378, 2017
Terminated and Tailbiting Spatially Coupled Codes With Optimized Bit Mappings for Spectrally Efficient Fiber-Optical Systems
C Häger, A Graell i Amat, F Brännström, A Alvarado, E Agrell
Journal of Lightwave Technology 33 (7), 1275-1285, 2015
Model-based machine learning for joint digital backpropagation and PMD compensation
RM Bütler, C Häger, HD Pfister, G Liga, A Alvarado
Journal of Lightwave Technology 39 (4), 949-959, 2020
Decoding Reed-Muller codes using minimum-weight parity checks
E Santi, C Hager, HD Pfister
2018 IEEE International Symposium on Information Theory (ISIT), 1296-1300, 2018
Decoding Reed–Muller codes using redundant code constraints
M Lian, C Häger, HD Pfister
2020 IEEE International Symposium on Information Theory (ISIT), 42-47, 2020
On the information loss of the max-log approximation in BICM systems
M Ivanov, C Häger, F Brännström, A Graell i Amat, A Alvarado, E Agrell
IEEE Transactions on Information Theory 62 (6), 3011-3025, 2016
On Parameter Optimization for Staircase Codes
C Häger, A Graell i Amat, HD Pfister, A Alvarado, F Brännström, E Agrell
Proc. Optical Fiber Communication Conf. and Exposition (OFC), 2015
On low-complexity decoding of product codes for high-throughput fiber-optic systems
A Sheikh, AG i Amat, G Liva, C Hager, HD Pfister
2018 IEEE 10th International Symposium on Turbo Codes & Iterative …, 2018
End-to-end learning for integrated sensing and communication
JM Mateos-Ramos, J Song, Y Wu, C Häger, MF Keskin, V Yajnanarayana, ...
ICC 2022-IEEE International Conference on Communications, 1942-1947, 2022
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