45 citations · 166 across the 16 of their papers we have counts for
5 papers · 1 filter
Novel Massive MIMO Channel Sounding Data Applied to Deep Learning-based Indoor Positioning
Maximilian Arnold, Jakob Hoydis, Stephan ten Brink
With a significant increase in area throughput, Massive MIMO has become an enabling technology for fifth generation (5G) wireless mobile communication systems. Although prototypes…
Subcarrier-Interlaced FDD for Faster-than-TDD Channel Tracking in Massive MIMO Systems
Maximilian Arnold, Xiaojie Wang, Stephan ten Brink
Canonical Massive MIMO uses time division duplex (TDD) to exploit channel reciprocity within the coherence time, avoiding feedback of channel state information (CSI), as is require…
Area Rate Evaluation based on Spatial Clustering of massive MIMO Channel Measurements
Maximilian Arnold, Johannes Pfeiffer, Stephan ten Brink
Channel models for massive MIMO are typically based on matrices with complex Gaussian entries, extended by the Kronecker and Weichselberger model. One reason for observing a gap be…
Evaluating Massive MIMO Precoding based on 3D-Channel Measurements with a Spider Antenna
Maximilian Arnold, Marc Gauger, Stephan ten Brink
Massive Multiple-Input Multiple-Output (MIMO)communications uses a large number of antennas at the base station to increase the data rate and user density in future wireless system…
On Deep Learning-based Massive MIMO Indoor User Localization
Maximilian Arnold, Sebastian Dörner, Sebastian Cammerer +1
We examine the usability of deep neural networks for multiple-input multiple-output (MIMO) user positioning solely based on the orthogonal frequency division multiplex (OFDM) compl…