429 citations · 939 across the 56 of their papers we have counts for
17 papers · 1 filter
Geometric Constellation Shaping with Low-complexity Demappers for Wiener Phase-noise Channels
Andrej Rode, Laurent Schmalen
We show that separating the in-phase and quadrature component in optimized, machine-learning based demappers of optical communications systems with geometric constellation shaping…
Neural Belief Propagation Decoding of Quantum LDPC Codes Using Overcomplete Check Matrices
Sisi Miao, Alexander Schnerring, Haizheng Li +1
The recent success in constructing asymptotically good quantum low-density parity-check (QLDPC) codes makes this family of codes a promising candidate for error-correcting schemes…
End-to-end Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search
Andrej Rode, Benedikt Geiger, Shrinivas Chimmalgi +1
As the demand for higher data throughput in coherent optical communication systems increases, we need to find ways to increase capacity in existing and future optical communication…
Semi-Deterministic Subspace Selection for Sparse Recursive Projection-Aggregation Decoding of Reed-Muller Codes
Johannes Voigt, Holger Jäkel, Laurent Schmalen
Recursive projection aggregation (RPA) decoding as introduced in [1] is a novel decoding algorithm which performs close to the maximum likelihood decoder for short-length Reed-Mull…
Structural Optimization of Factor Graphs for Symbol Detection via Continuous Clustering and Machine Learning
Lukas Rapp, Luca Schmid, Andrej Rode +1
We propose a novel method to optimize the structure of factor graphs for graph-based inference. As an example inference task, we consider symbol detection on linear inter-symbol in…
Spiking Neural Network Decision Feedback Equalization
Eike-Manuel Bansbach, Alexander von Bank, Laurent Schmalen
In the past years, artificial neural networks (ANNs) have become the de-facto standard to solve tasks in communications engineering that are difficult to solve with traditional met…
Blind and Channel-agnostic Equalization Using Adversarial Networks
Vincent Lauinger, Manuel Hoffmann, Jonas Ney +2
Due to the rapid development of autonomous driving, the Internet of Things and streaming services, modern communication systems have to cope with varying channel conditions and a s…
Deep Reinforcement Learning for Uplink Multi-Carrier Non-Orthogonal Multiple Access Resource Allocation Using Buffer State Information
Eike-Manuel Bansbach, Yigit Kiyak, Laurent Schmalen
For orthogonal multiple access (OMA) systems, the number of served user equipments (UEs) is limited to the number of available orthogonal resources. On the other hand, non-orthogon…
Improved Soft-aided Decoding of Product Codes with Adaptive Performance-Complexity Trade-off
Sisi Miao, Lukas Rapp, Laurent Schmalen
We propose an improved soft-aided decoding scheme for product codes that approaches the decoding performance of conventional soft-decision TPD with only a 0.2 dB gap while keeping…
Optimization of Geometric Constellation Shaping for Wiener Phase Noise Channels with Varying Channel Parameters
Andrej Rode, Laurent Schmalen
We present a novel method to investigate the effects of varying channel parameters on geometrically shaped constellations for communication systems employing the blind phase search…
Distributed Transmission and Spatially Coupled Forward Error Correction in Regenerative Multipoint-to-Point Networks
Laurent Schmalen, Tobias A. Eriksson, Fred Buchali +2
We investigate the performance of coded modulation for multi-hop regenerative optical networks. We analyze options for computing decoder input LLRs, show reach increases by optimiz…
Performance Metrics for Communication Systems with Forward Error Correction
Laurent Schmalen
We revisit performance metrics for optical communication systems with FEC. We illustrate the concept of universality and discuss the most widespread performance thresholds. Finally…
Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoders
Vincent Lauinger, Fred Buchali, Laurent Schmalen
We investigate the potential of adaptive blind equalizers based on variational inference for carrier recovery in optical communications. These equalizers are based on a low-complex…
Improved Soft-aided Decoding of Product Codes with Dynamic Reliability Scores
Sisi Miao, Lukas Rapp, Laurent Schmalen
Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss co…
Low-complexity Near-optimum Symbol Detection Based on Neural Enhancement of Factor Graphs
Luca Schmid, Laurent Schmalen
We consider the application of the factor graph framework for symbol detection on linear inter-symbol interference channels. Based on the Ungerboeck observation model, a detection…
Neural Enhancement of Factor Graph-based Symbol Detection
Luca Schmid, Laurent Schmalen
We study the application of the factor graph framework for symbol detection on linear inter-symbol interference channels. Cyclic factor graphs have the potential to yield low-compl…
Error-and-erasure Decoding of Product and Staircase Codes with Simplified Extrinsic Message Passing
Sisi Miao, Lukas Rapp, Laurent Schmalen
The decoding performance of product codes and staircase codes based on iterative bounded-distance decoding (iBDD) can be improved with the aid of a moderate amount of soft informat…