activity
20152023
most citedBlind Channel Equalization Using Vector-Quantized Variational Autoencoders

3 citations · 13 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2023

Local Message Passing on Frustrated Systems

Luca Schmid, Joshua Brenk, Laurent Schmalen

Message passing on factor graphs is a powerful framework for probabilistic inference, which finds important applications in various scientific domains. The most wide-spread message…

eess.SP20232 cited

Bistatic OFDM-based Joint Radar-Communication: Synchronization, Data Communication and Sensing

Lucas Giroto de Oliveira, David Brunner, Axel Diewald +4

This article introduces a bistatic joint radar-communication (RadCom) system based on orthogonal frequency-division multiplexing (OFDM). In this context, the adopted OFDM frame str…

cs.NE2023

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…

eess.SP20233 cited

Blind Channel Equalization Using Vector-Quantized Variational Autoencoders

Jinxiang Song, Vincent Lauinger, Yibo Wu +5

State-of-the-art high-spectral-efficiency communication systems employ high-order modulation formats coupled with high symbol rates to accommodate the ever-growing demand for data…

eess.SP20233 cited

Autoencoder-based Joint Communication and Sensing of Multiple Targets

Charlotte Muth, Laurent Schmalen

We investigate the potential of autoencoders (AEs) for building a joint communication and sensing (JCAS) system that enables communication with one user while detecting multiple ra…

eess.SP2023

Improving the Bootstrap of Blind Equalizers with Variational Autoencoders

Vincent Lauinger, Fred Buchali, Laurent Schmalen

We evaluate the start-up of blind equalizers at critical working points, analyze the advantages and obstacles of commonly-used algorithms, and demonstrate how the recently-proposed…