1 citations · 1 across the 2 of their papers we have counts for
2 papers
eess.SP2025★ 1 cited
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer +2
Learning the site-specific distribution of the wireless channel within a particular environment of interest is essential to exploit the full potential of machine learning (ML) for…
cs.IT2023
A Neural Receiver for 5G NR Multi-user MIMO
Sebastian Cammerer, Fayçal Aït Aoudia, Jakob Hoydis +4
We introduce a neural network (NN)-based multiuser multiple-input multiple-output (MU-MIMO) receiver with 5G New Radio (5G NR) physical uplink shared channel (PUSCH) compatibility.…