48 citations · 54 across the 11 of their papers we have counts for
25 papers
FPGA Implementation of Multi-Layer Machine Learning Equalizer with On-Chip Training
Keren Liu, Erik Börjeson, Christian Häger +1
We design and implement an adaptive machine learning equalizer that alternates multiple linear and nonlinear computational layers on an FPGA. On-chip training via gradient backprop…
End-to-End Learning for Integrated Sensing and Communication
José Miguel Mateos-Ramos, Jinxiang Song, Yibo Wu +4
Integrated sensing and communication (ISAC) aims to unify radar and communication systems through a combination of joint hardware, joint waveforms, joint signal design, and joint s…
Over-the-fiber Digital Predistortion Using Reinforcement Learning
Jinxiang Song, Zonglong He, Christian Häger +4
We demonstrate, for the first time, experimental over-the-fiber training of transmitter neural networks (NNs) using reinforcement learning. Optical back-to-back training of a novel…
Autoencoder-Based Unequal Error Protection Codes
Vukan Ninkovic, Dejan Vukobratovic, Christian Häger +2
We present a novel autoencoder-based approach for designing codes that provide unequal error protection (UEP) capabilities. The proposed design is based on a generalization of an a…
End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairment
Jinxiang Song, Christian Häger, Jochen Schröder +2
We propose an end-to-end learning-based approach for superchannel systems impaired by non-ideal hardware component. Our system achieves up to 60% SER reduction and up to 50% guard…
Pruning and Quantizing Neural Belief Propagation Decoders
Andreas Buchberger, Christian Häger, Henry D. Pfister +2
We consider near maximum-likelihood (ML) decoding of short linear block codes. In particular, we propose a novel decoding approach based on neural belief propagation (NBP) decoding…