28 citations · 51 across the 13 of their papers we have counts for
13 papers
Joint Probabilistic and Geometric Constellation Shaping for Complexity-Constrained Direct Detection Optical Systems
Rodrigo Fischer, Shrinivas Chimmalgi, Andrej Rode +1
We evaluate joint probabilistic and geometric constellation shaping via reinforcement learning for complexity-constrained joint equalization and demodulation of direct detection op…
An Extension of Enumerative Sphere Shaping for Arbitrary Channel Input Distributions
Frederik Ritter, Andrej Rode, Laurent Schmalen
A non-uniform channel input distribution is key for achieving the capacity of arbitrary channels. However, message bits are generally assumed to follow a uniform distribution which…
Novel Phase-Noise-Tolerant Variational-Autoencoder-Based Equalization Suitable for Space-Division-Multiplexed Transmission
Vincent Lauinger, Lennart Schmitz, Patrick Matalla +3
We demonstrate the effectiveness of a novel phase-noise-tolerant, variational-autoencoder-based equalization scheme for space-division-multiplexed (SDM) transmission in an experime…
Constellation Shaping for OFDM-ISAC Systems: From Theoretical Bounds to Practical Implementation
Benedikt Geiger, Fan Liu, Shihang Lu +4
Integrated sensing and communications (ISAC) promises new use cases for mobile communication systems by reusing the communication signal for radar-like sensing. However, sensing an…
Joint Optimization of Geometric and Probabilistic Constellation Shaping for OFDM-ISAC Systems
Benedikt Geiger, Fan Liu, Shihang Lu +2
6G communications systems are expected to integrate radar-like sensing capabilities enabling novel use cases. However, integrated sensing and communications (ISAC) introduces a tra…
Introducing RSESS: An Open Source Enumerative Sphere Shaping Implementation Coded in Rust
Frederik Ritter, Andrej Rode, Laurent Schmalen
In this work, we present an open-source implementation of the enumerative sphere shaping (ESS) algorithm used for probabilistic constellation shaping (PCS). PCS aims at closing the…
Approximate Maximum a Posteriori Carrier Phase Estimator for Wiener Phase Noise Channels using Belief Propagation
Shrinivas Chimmalgi, Andrej Rode, Luca Schmid +1
The blind phase search (BPS) algorithm for carrier phase estimation is known to have sub-optimal performance for probabilistically shaped constellations. We present a belief propag…
Optimized Geometric Constellation Shaping for Wiener Phase Noise Channels with Viterbi-Viterbi Carrier Phase Estimation
Andrej Rode, Wintana Araya Gebrehiwot, Shrinivas Chimmalgi +1
The Viterbi & Viterbi (V&V) algorithm is well understood for QPSK and 16-QAM, but modifications are required for higher-order modulation formats. We present an approach to extend t…
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…
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…
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…
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…
Geometric Constellation Shaping for Phase-noise Channels Using a Differentiable Blind Phase Search
Andrej Rode, Benedikt Geiger, Laurent Schmalen
We perform geometric constellation shaping with optimized bit labeling using a binary autoencoder including a differential blind phase search (BPS). Our approach enables full end-t…