collaborators

5 papers

eess.SP2026

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…

cs.IT2026

A Tensor-Train Framework for Bayesian Inference in High-Dimensional Systems: Applications to MIMO Detection and Channel Decoding

Luca Schmid, Dominik Sulz, Shrinivas Chimmalgi +1

Bayesian inference in high-dimensional discrete-input additive noise models is a fundamental challenge in communication systems, as the support of the required joint a posteriori p…

eess.SP2026

Precoding Design for Multi-User MIMO Joint Communications and Sensing

Charlotte Muth, Shrinivas Chimmalgi, Laurent Schmalen

We investigate precoding for multi-user (MU) multiple-input multiple-output (MIMO) joint communications and sensing (JCAS) systems, taking into account the potential interference b…

cs.IT2025

End-to-End Learning of Probabilistic Constellation Shaping through Importance Sampling

Shrinivas Chimmalgi, Laurent Schmalen, Vahid Aref

Probabilistic constellation shaping enables easy rate adaption and has been proven to reduce the gap to Shannon capacity. Constellation point probabilities are optimized to maximiz…

eess.SP2025

Improved Estimation Accuracy in OFDM-based Joint Communication and Sensing through Kalman Tracking and Interpolation

Charlotte Muth, Leon Schmidt, Shrinivas Chimmalgi +1

We investigate a monostatic orthogonal frequency-division multiplexing (OFDM)-based joint communication and sensing (JCAS) system for object tracking. Our setup consists of a trans…