| 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 | 39 | 2022 |
| End-to-end learning for VCSEL-based optical interconnects: state-of-the-art, challenges, and opportunities M Srinivasan, J Song, A Grabowski, K Szczerba, HK Iversen, MN Schmidt, ... Journal of Lightwave Technology 41 (11), 3261-3277, 2023 | 25 | 2023 |
| Model-Based End-to-End Learning for WDM Systems With Transceiver Hardware Impairments J Song, C Häger, J Schröder, A Graell i Amat, H Wymeersch arXiv preprint arXiv:2111.14515, 2021 | 22 | 2021 |
| Benchmarking End-to-end Learning of MIMO Physical-Layer Communication J Song, C Häger, J Schröder, T O'Shea, H Wymeersch IEEE Global Communications Conference 2020, 1-6, 2020 | 22 | 2020 |
| Benchmarking and interpreting end-to-end learning of MIMO and multi-user communication J Song, C Häger, J Schröder, TJ O’Shea, E Agrell, H Wymeersch IEEE Transactions on Wireless Communications 21 (9), 7287-7298, 2022 | 20 | 2022 |
| End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairment J Song, C Häger, J Schröder, A Graell i Amat, H Wymeersch arXiv preprint arXiv:2103.15856, 2021 | 19 | 2021 |
| Over-the-fiber Digital Predistortion Using Reinforcement Learning J Song, Z He, C Häger, M Karlsson, A Graell i Amat, H Wymeersch, ... arXiv preprint arXiv:2106.04934, 2021 | 18 | 2021 |
| Spatial signal design for positioning via end-to-end learning S Rivetti, JM Mateos-Ramos, Y Wu, J Song, MF Keskin, V Yajnanarayana, ... IEEE Wireless Communications Letters 12 (3), 525-529, 2023 | 14 | 2023 |
| Learning physical-layer communication with quantized feedback J Song, B Peng, C Häger, H Wymeersch, A Sahai IEEE Transactions on Communications 68 (1), 645-653, 2019 | 12 | 2019 |
| Periodicity-enabled size reduction of symbol based predistortion for high-order QAM Z He, J Song, K Vijayan, C Häger, AG i Amat, H Wymeersch, ... Journal of Lightwave Technology 40 (18), 6168-6178, 2022 | 10 | 2022 |
| Symbol-Based Over-the-Air Digital Predistortion Using Reinforcement Learning Y Wu, J Song, C Häger, U Gustavsson, A Graell i Amat, H Wymeersch arXiv preprint arXiv:2111.11923, 2021 | 9 | 2021 |
| Symbol-based supervised learning predistortion for compensating transmitter nonlinearity Z He, J Song, C Häger, K Vijayan, P Andrekson, M Karlsson, AG i Amat, ... 2021 European Conference on Optical Communication (ECOC), 1-4, 2021 | 9 | 2021 |
| Blind Channel Equalization Using Vector-Quantized Variational Autoencoders J Song, V Lauinger, Y Wu, C Häger, J Schröder, A Grell i Amat, ... arXiv preprint arXiv:2302.11687, 2023 | 8 | 2023 |
| Learning optimal PAM levels for VCSEL-based optical interconnects M Srinivasan, J Song, C Häger, K Szczerba, H Wymeersch, J Schröder 2022 European Conference on Optical Communication (ECOC), 1-4, 2022 | 6 | 2022 |
| Experimental demonstration of learned pulse shaping filter for superchannels Z He, J Song, C Häger, AG i Amat, H Wymeersch, PA Andrekson, ... Optical Fiber Communication Conference, W2A. 33, 2022 | 5 | 2022 |
| Blind frequency-domain equalization using vector-quantized variational autoencoders J Song, V Lauinger, C Häger, J Schröder, AG i Amat, L Schmalen, ... 49th European Conference on Optical Communications (ECOC 2023) 2023, 1222-1225, 2023 | 3 | 2023 |
| Autoencoders for Physical-Layer Communications: Approaches and Applications J Song PQDT-Global, 2023 | 1 | 2023 |
| Data-driven learning of fiber-optic communication systems with quantized feedback J Song | | 2019 |
Christian HägerAssistant Professor, Chalmers University of Technolgy, Department of Electrical EngineeringPreverjeni e-poštni naslov na chalmers.se