4 papers · 1 filter
Information Rates of Approximate Message Passing for Bandlimited Direct-Detection Channels
Daniel Plabst, Mohamed Akrout, Tobias Prinz +2
The capacity of bandlimited direct-detection channels is challenging to compute or approach due to the receiver non-linearity. A generalized vector approximate message passing (GVA…
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…
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…
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…