4 papers · 1 filter
Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity
Daniel Plabst, Tobias Prinz, Francesca Diedolo +4
Neural networks (NNs) inspired by the forward-backward algorithm (FBA) are used as equalizers for bandlimited channels with a memoryless nonlinearity. The NN-equalizers are combine…
Optimizing Bipolar Constellations for High-Rate Transmission in Short-Reach Fiber Links with Direct Detection
Thomas Wiegart, Daniel Plabst, Norbert Hanik +1
Bipolar modulation increases the achievable information rate of communication links with direct-detection receivers. This paper optimizes bipolar transmission with a modulator bias…
Neural Network-Based Successive Interference Cancellation for Non-Linear Bandlimited Channels
Daniel Plabst, Tobias Prinz, Francesca Diedolo +4
Reliable communication over bandlimited and non-linear channels usually requires equalization to simplify receiver processing. Equalizers that perform joint detection and decoding…
Successive Interference Cancellation for Bandlimited Channels with Direct Detection
Tobias Prinz, Daniel Plabst, Thomas Wiegart +3
The maximum information rates for bandlimited channels with direct detection are achieved with joint detection and decoding (JDD), but JDD is often too complex to implement. Two re…