activity
20132022
most citedMachine Learning for Model Order Selection in MIMO OFDM Systems

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2022

Combining AI/ML and PHY Layer Rule Based Inference -- Some First Results

Brenda Vilas Boas, Wolfgang Zirwas, Martin Haardt

In 3GPP New Radio (NR) Release 18 we see the first study item starting in May 2022, which will evaluate the potential of AI/ML methods for Radio Access Network (RAN) 1, i.e., for m…

eess.SP20211 cited

Machine Learning for Model Order Selection in MIMO OFDM Systems

Brenda Vilas Boas, Wolfgang Zirwas, Martin Haardt

A variety of wireless channel estimation methods, e.g., MUSIC and ESPRIT, rely on prior knowledge of the model order. Therefore, it is important to correctly estimate the number of…

cs.IT2018

Analysis of Massive MIMO and Base Station Cooperation in an Indoor Scenario

Stefan Dierks, Gerhard Kramer, Berthold Panzner +1

The performance of centralized and distributed massive MIMO deployments are analyzed for indoor office scenarios. The distributed deployments use one of the following precoding met…

cs.IT2017

Constructing Receiver Signal Points using Constrained Massive MIMO Arrays

Markus Staudacher, Gerhard Kramer, Wolfgang Zirwas +2

A low cost solution for constructing receiver signal points is investigated that combines a large number of constrained radio frequency (RF) frontends with a limited number of full…

cs.IT2013

Feasibility Conditions of Interference Alignment via Two Orthogonal Subcarriers

Stefan Dierks, Gerhard Kramer, Wolfgang Zirwas

Conditions are derived on line-of-sight channels to ensure the feasibility of interference alignment. The conditions involve choosing only the spacing between two subcarriers of an…