2 citations · 3 across the 9 of their papers we have counts for
6 papers · 1 filter
Short-reach Optical Communications: A Real-world Task for Neuromorphic Hardware
Elias Arnold, Eike-Manuel Edelmann, Alexander von Bank +3
Spiking neural networks (SNNs) emulated on dedicated neuromorphic accelerators promise to offer energy-efficient signal processing. However, the neuromorphic advantage over traditi…
Non-linear Equalization in 112 Gb/s PONs Using Kolmogorov-Arnold Networks
Rodrigo Fischer, Patrick Matalla, Sebastian Randel +1
We investigate Kolmogorov-Arnold networks (KANs) for non-linear equalization of 112 Gb/s PAM4 passive optical networks (PONs). Using pruning and extensive hyperparameter search, we…
Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications
Laurent Schmalen, Vincent Lauinger, Jonas Ney +5
In this paper, we highlight recent advances in the use of machine learning for implementing equalizers for optical communications. We highlight both algorithmic advances as well as…
CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture
Jonas Ney, Christoph Füllner, Vincent Lauinger +3
To satisfy the growing throughput demand of data-intensive applications, the performance of optical communication systems increased dramatically in recent years. With higher throug…
Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications
Jonas Ney, Patrick Matalla, Vincent Lauinger +3
In this work, we present a high-throughput field programmable gate array (FPGA) demonstrator of an artificial neural network (ANN)-based equalizer. The equalization is performed an…
Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks
Vincent Lauinger, Patrick Matalla, Jonas Ney +3
We demonstrate and evaluate a fully-blind digital signal processing (DSP) chain for 100G passive optical networks (PONs), and analyze different equalizer topologies based on neural…