Constellation optimization for coherent optical channels distorted by nonlinear phase noise. - Christian Häger; Alexandre Graell i Amat; Alex Alvarado; Erik Agrell (GLOBECOM, 2012)

Design of APSK Constellations for Coherent Optical Channels with Nonlinear Phase Noise. - Christian Häger; Alexandre Graell i Amat; Alex Alvarado; Erik Agrell (IEEE Trans. Commun., 2013)

Comparison of terminated and tailbiting spatially coupled LDPC codes with optimized bit mapping for PM-64-QAM. - Christian Häger; Alexandre Graell i Amat; Fredrik Brannstrom; Alex Alvarado; Erik Agrell (ECOC, 2014)

Optimized bit mappings for spatially coupled LDPC codes over parallel binary erasure channels. - Christian Häger; Alexandre Graell i Amat; Alex Alvarado; Fredrik Brannstrom; Erik Agrell (ICC, 2014)

Improving Soft FEC Performance for Higher-Order Modulations by Bit Mapper Optimization. - Christian Häger; Alexandre Graell i Amat; Fredrik Brännström; Alex Alvarado; Erik Agrell (CoRR, 2014)

Terminated and Tailbiting Spatially Coupled Codes with Optimized Bit Mappings for Spectrally Efficient Fiber-Optical Systems. - Christian Häger; Alexandre Graell i Amat; Fredrik Brännström; Alex Alvarado; Erik Agrell (CoRR, 2014)

A Low-Complexity Detector for Memoryless Polarization-Multiplexed Fiber-Optical Channels. - Christian Häger; Lotfollah Beygi; Erik Agrell; Pontus Johannisson; Magnus Karlsson 001; Alexandre Graell i Amat (IEEE Commun. Lett., 2014)

On parameter optimization for staircase codes. - Christian Häger; Alexandre Graell i Amat; Henry D. Pfister; Alex Alvarado; Fredrik Brannstrom; Erik Agrell (OFC, 2015)

Density Evolution for Deterministic Generalized Product Codes on the Binary Erasure Channel. - Christian Häger; Henry D. Pfister; Alexandre Graell i Amat; Fredrik Brännström (CoRR, 2015)

Deterministic and ensemble-based spatially-coupled product codes. - Christian Häger; Henry D. Pfister; Alexandre Graell i Amat; Fredrik Brannstrom (ISIT, 2016)

Density evolution for deterministic generalized product codes with higher-order modulation. - Christian Häger; Alexandre Graell i Amat; Henry D. Pfister; Fredrik Brannstrom (ISTC, 2016)

Density evolution and error floor analysis for staircase and braided codes. - Christian Häger; Henry D. Pfister; Alexandre Graell i Amat; Fredrik Brannstrom (OFC, 2016)

On the Information Loss of the Max-Log Approximation in BICM Systems. - Mikhail Ivanov; Christian Häger; Fredrik Brannstrom; Alexandre Graell i Amat; Alex Alvarado; Erik Agrell (IEEE Trans. Inf. Theory, 2016)

Analysis and Design of Spatially-Coupled Codes with Application to Fiber-Optical Communications. - Christian Häger (2016)

Miscorrection-free Decoding of Staircase Codes. - Christian Häger; Henry D. Pfister (ECOC, 2017)

Approaching Miscorrection-free Performance of Product and Generalized Product Codes. - Christian Häger; Henry D. Pfister (CoRR, 2017)

Density Evolution for Deterministic Generalized Product Codes on the Binary Erasure Channel at High Rates. - Christian Häger; Henry D. Pfister; Alexandre Graell i Amat; Fredrik Brannstrom (IEEE Trans. Inf. Theory, 2017)

ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters. - Christoffer Fougstedt; Christian Häger; Lars J. Svensson; Henry D. Pfister; Per Larsson-Edefors (ECOC, 2018)

Wideband Time-Domain Digital Backpropagation via Subband Processing and Deep Learning. - Christian Häger; Henry D. Pfister (ECOC, 2018)

Achievable Information Rates for Nonlinear Fiber Communication via End-to-end Autoencoder Learning. - Shen Li; Christian Häger; Nil Garcia; Henk Wymeersch (ECOC, 2018)

Deep Learning of the Nonlinear Schrödinger Equation in Fiber-Optic Communications. - Christian Häger; Henry D. Pfister (ISIT, 2018)

Decoding Reed-Muller Codes Using Minimum- Weight Parity Checks. - Elia Santi; Christian Häger; Henry D. Pfister (ISIT, 2018)

On Low-Complexity Decoding of Product Codes for High-Throughput Fiber-Optic Systems. - Alireza Sheikh; Alexandre Graell i Amat; Gianluigi Liva; Christian Häger; Henry D. Pfister (ISTC, 2018)

What Can Machine Learning Teach Us about Communications? - Mengke Lian; Christian Häger; Henry D. Pfister (ITW, 2018)

Nonlinear Interference Mitigation via Deep Neural Networks. - Christian Häger; Henry D. Pfister (OFC, 2018)

Approaching Miscorrection-Free Performance of Product Codes With Anchor Decoding. - Christian Häger; Henry D. Pfister (IEEE Trans. Commun., 2018)

Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding. - Fabrizio Carpi; Christian Häger; Marco Martalò; Riccardo Raheli; Henry D. Pfister (Allerton, 2019)

Learned Belief-Propagation Decoding with Simple Scaling and SNR Adaptation. - Mengke Lian; Fabrizio Carpi; Christian Häger; Henry D. Pfister (ISIT, 2019)

Revisiting Multi-Step Nonlinearity Compensation with Machine Learning. - Christian Häger; Henry D. Pfister; Rick M. Bütler; Gabriele Liga; Alex Alvarado (CoRR, 2019)

Benchmarking End-to-end Learning of MIMO Physical-Layer Communication. - Jinxiang Song; Christian Häger; Jochen Schröder; Tim O'Shea 001; Henk Wymeersch (GLOBECOM, 2020)

Pruning Neural Belief Propagation Decoders. - Andreas Buchberger; Christian Häger; Henry D. Pfister; Laurent Schmalen; Alexandre Graell i Amat (ISIT, 2020)

Decoding Reed-Muller Codes Using Redundant Code Constraints. - Mengke Lian; Christian Häger; Henry D. Pfister (ISIT, 2020)

End-to-End Learning of Geometrical Shaping Maximizing Generalized Mutual Information. - Kadir Gümüs; Alex Alvarado; Bin Chen 006; Christian Häger; Erik Agrell (OFC, 2020)

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation. - Christian Häger; Henry D. Pfister; Rick M. Bütler; Gabriele Liga; Alex Alvarado (OFC, 2020)

Learned Decimation for Neural Belief Propagation Decoders. - Andreas Buchberger; Christian Häger; Henry D. Pfister; Laurent Schmalen; Alexandre Graell i Amat (CoRR, 2020)

Learning Physical-Layer Communication With Quantized Feedback. - Jinxiang Song; Bile Peng; Christian Häger; Henk Wymeersch; Anant Sahai (IEEE Trans. Commun., 2020)

Symbol-Based Supervised Learning Predistortion for Compensating Transmitter Nonlinearity. - Zonglong He; Jinxiang Song; Christian Häger; Kovendhan Vijayan; Peter A. Andrekson; Magnus Karlsson 001; Alexandre Graell i Amat; Henk Wymeersch; Jochen Schröder (ECOC, 2021)

Over-the-fiber Digital Predistortion Using Reinforcement Learning. - Jinxiang Song; Zonglong He; Christian Häger; Magnus Karlsson 001; Alexandre Graell i Amat; Henk Wymeersch; Jochen Schröder (ECOC, 2021)

Learned Decimation for Neural Belief Propagation Decoders : Invited Paper. - Andreas Buchberger; Christian Häger; Henry D. Pfister; Laurent Schmalen; Alexandre Graell i Amat (ICASSP, 2021)

End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairment. - Jinxiang Song; Christian Häger; Jochen Schröder; Alexandre Graell i Amat; Henk Wymeersch (OFC, 2021)

Autoencoder-Based Unequal Error Protection Codes. - Vukan Ninkovic; Dejan Vukobratovic; Christian Häger; Henk Wymeersch; Alexandre Graell i Amat (IEEE Commun. Lett., 2021)

Pruning and Quantizing Neural Belief Propagation Decoders. - Andreas Buchberger; Christian Häger; Henry D. Pfister; Laurent Schmalen; Alexandre Graell i Amat (IEEE J. Sel. Areas Commun., 2021)

Physics-Based Deep Learning for Fiber-Optic Communication Systems. - Christian Häger; Henry D. Pfister (IEEE J. Sel. Areas Commun., 2021)

End-to-End Learning for Integrated Sensing and Communication. - José Miguel Mateos-Ramos; Jinxiang Song; Yibo Wu; Christian Häger; Musa Furkan Keskin; Vijaya Yajnanarayana; Henk Wymeersch (ICC, 2022)

Symbol-Based Over-the-Air Digital Predistortion Using Reinforcement Learning. - Yibo Wu; Jinxiang Song; Christian Häger; Ulf Gustavsson; Alexandre Graell i Amat; Henk Wymeersch (ICC, 2022)

Experimental Demonstration of Learned Pulse Shaping Filter for Superchannels. - Zonglong He; Jinxiang Song; Christian Häger; Alexandre Graell i Amat; Henk Wymeersch; Peter A. Andrekson; Magnus Karlsson 001; Jochen Schröder (OFC, 2022)

Data-Driven Upper Bounds on Channel Capacity. - Christian Häger; Erik Agrell (CoRR, 2022)

End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities. - Muralikrishnan Srinivasan; Jinxiang Song; Alexander Grabowski; Krzysztof Szczerba; Holger K. Iversen; Mikkel N. Schmidt; Darko Zibar; Jochen Schröder; Anders Larsson; Christian Häger; Henk Wymeersch (CoRR, 2022)

Data-Driven Estimation of Capacity Upper Bounds. - Christian Häger; Erik Agrell (IEEE Commun. Lett., 2022)

Benchmarking and Interpreting End-to-End Learning of MIMO and Multi-User Communication. - Jinxiang Song; Christian Häger; Jochen Schröder; Timothy J. O'Shea; Erik Agrell; Henk Wymeersch (IEEE Trans. Wirel. Commun., 2022)

Model-Driven End-to-End Learning for Integrated Sensing and Communication. - José Miguel Mateos-Ramos; Christian Häger; Musa Furkan Keskin; Luc Le Magoarou; Henk Wymeersch (ICC, 2023)

Rateless Autoencoder Codes: Trading off Decoding Delay and Reliability. - Vukan Ninkovic; Dejan Vukobratovic; Christian Häger; Henk Wymeersch; Alexandre Graell i Amat (ICC, 2023)

Deep-Learning-Based Channel Estimation for Distributed MIMO with 1-bit Radio-Over-Fiber Fronthaul. - Alireza Bordbar; Lise Aabel; Christian Häger; Christian Fager; Giuseppe Durisi (ISWCS, 2023)

FPGA Implementation of Multi-Layer Machine Learning Equalizer with On-Chip Training. - Keren Liu; Erik Börjeson; Christian Häger; Per Larsson-Edefors (OFC, 2023)

Spatial Signal Design for Positioning via End-to-End Learning. - Steven Rivetti; José Miguel Mateos-Ramos; Yibo Wu; Jinxiang Song; Musa Furkan Keskin; Vijaya Yajnanarayana; Christian Häger; Henk Wymeersch (IEEE Wirel. Commun. Lett., 2023)

Decoding Quantum LDPC Codes Using Graph Neural Networks. - Vukan Ninkovic; Ognjen Kundacina; Dejan Vukobratovic; Christian Häger; Alexandre Graell i Amat (GLOBECOM, 2024)

Belief Propagation Decoding of Quantum LDPC Codes with Guided Decimation. - Hanwen Yao; Waleed Abu Laban; Christian Häger; Alexandre Graell i Amat; Henry D. Pfister (ISIT, 2024)

Real-Time Implementation of Machine-Learning DSP. - Erik Börjeson; Keren Liu; Christian Häger; Per Larsson-Edefors (OFC, 2024)

Learning to Extract Distributed Polarization Sensing Data from Noisy Jones Matrices. - Mohammad Farsi 003; Christian Häger; Magnus Karlsson 001; Erik Agrell (OFC, 2024)

Physically Parameterized Differentiable MUSIC for DoA Estimation with Uncalibrated Arrays. - Baptiste Chatelier; José Miguel Mateos-Ramos; Vincent Corlay; Christian Häger; Matthieu Crussière; Henk Wymeersch; Luc Le Magoarou (CoRR, 2024)

Unsupervised Learning for Gain-Phase Impairment Calibration in ISAC Systems. - José Miguel Mateos-Ramos; Christian Häger; Musa Furkan Keskin; Luc Le Magoarou; Henk Wymeersch (ICASSP, 2025)

Model-Based End-to-End Learning for Multi-Target Integrated Sensing and Communication Under Hardware Impairments. - José Miguel Mateos-Ramos; Christian Häger; Musa Furkan Keskin; Luc Le Magoarou; Henk Wymeersch (IEEE Trans. Wirel. Commun., 2025)

Rate-Limited Closed-Loop Distributed ISAC Systems: An Autoencoder Approach. - Guangjin Pan; Zhixing Li; Ayça Özçelikkale; Christian Häger; Musa Furkan Keskin; Henk Wymeersch (CoRR, 2025)

Inverse Modeling of Dielectric Response in Time Domain using Physics-Informed Neural Networks. - Emir Esenov; Olof Hjortstam; Yuriy Serdyuk; Thomas Hammarström; Christian Häger (CoRR, 2025)

Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks. - Guangjin Pan; Kaixuan Huang; Hui Chen 014; Shunqing Zhang; Christian Häger; Henk Wymeersch (CoRR, 2025)