2 citations · 3 across the 9 of their papers we have counts for
12 papers
Spiking Neural Network-based Equalization and Demapping in IM/DD Systems: A Comparison
Eike-Manuel Edelmann, Alexander von Bank, Laurent Schmalen
In recent years, artificial neural networks (ANNs) have emerged as the de facto standard for addressing challenging problems in communications engineering that are difficult to sol…
Joint Probabilistic and Geometric Constellation Shaping for Complexity-Constrained Direct Detection Optical Systems
Rodrigo Fischer, Shrinivas Chimmalgi, Andrej Rode +1
We evaluate joint probabilistic and geometric constellation shaping via reinforcement learning for complexity-constrained joint equalization and demodulation of direct detection op…
Novel Phase-Noise-Tolerant Variational-Autoencoder-Based Equalization Suitable for Space-Division-Multiplexed Transmission
Vincent Lauinger, Lennart Schmitz, Patrick Matalla +3
We demonstrate the effectiveness of a novel phase-noise-tolerant, variational-autoencoder-based equalization scheme for space-division-multiplexed (SDM) transmission in an experime…
Encoding Optimization for Low-Complexity Spiking Neural Network Equalizers in IM/DD Systems
Eike-Manuel Edelmann, Alexander von Bank, Laurent Schmalen
Neural encoding parameters for spiking neural networks (SNNs) are typically set heuristically. We propose a reinforcement learning-based algorithm to optimize them. Applied to an S…
A Temporal Gaussian Noise Model for Equalization-enhanced Phase Noise
Benedikt Geiger, Fred Buchali, Vahid Aref +1
Equalization-enhanced Phase Noise causes burst-like distortions in high symbol-rate transmission systems. We propose a temporal Gaussian noise model that captures these distortions…
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…
Energy-efficient Spiking Neural Network Equalization for IM/DD Systems with Optimized Neural Encoding
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen
We propose an energy-efficient equalizer for IM/DD systems based on spiking neural networks. We optimize a neural spike encoding that boosts the equalizer's performance while decre…