5 papers
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…
Spiking Neural Belief Propagation Decoder for LDPC Codes with Small Variable Node Degrees
Alexander von Bank, Eike-Manuel Edelmann, Jonathan Mandelbaum +1
Spiking neural networks (SNNs) promise energy-efficient data processing by imitating the event-based behavior of biological neurons. In previous work, we introduced the enlarge-lik…
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…
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…
Spiking Neural Network Decision Feedback Equalization for IM/DD Systems
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen
A spiking neural network (SNN) equalizer with a decision feedback structure is applied to an IM/DD link with various parameters. The SNN outperforms linear and artificial neural ne…