Paper Info
Title
Evaluating massive MIMO precoding based on 3D-channel measurements with a spider antenna
Abstract
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 systems. For simulation, it has become common practice to use i.i.d. complex Gaussian matrix entries to obtain an average MIMO channel behavior. More refined models have been devised and proposed to standardization bodies; yet, channel modeling remains an active area of research, as current models tend to be, still, quite limited, e.g., when it comes to evaluating clustering algorithms, with regions of spatial orthogonality for concurrent scheduling of users, which is an essential concept in massive MIMO precoding. For this, spatial correlations need to be included. To further refine channel modeling, we have built a “spider antenna” prototype that allows spatially continuous measurements in three dimensions, enabling a high-resolution channel sampling over, initially, a volume of 2m × 2m × 2m for indoor measurements. Several experiments have been conducted to illustrate the new insights to be gained when studying user orthogonality, clustering and precoding in a massive MIMO context. Furthermore, the influence of antenna array geometry and user spacing on the achievable rate over actually measured channels is studied.
Year
DOI
Venue
2018
10.1109/ISWCS.2017.8108098
2017 International Symposium on Wireless Communication Systems (ISWCS)
Keywords
DocType
Volume
3D-channel measurements,Massive Multiple-Input Multiple-Output,base station,size 2.0 m,user orthogonality,massive MIMO precoding evaluation,user spacing,antenna array geometry,indoor measurements,high-resolution channel sampling,spatially continuous measurements,spider antenna prototype,refine channel modeling,spatial correlations,spatial orthogonality,average MIMO channel behavior,complex Gaussian matrix entries,future wireless systems,user density,data rate
Journal
abs/1804.05881
ISSN
ISBN
Citations 
2154-0217
978-1-5386-2914-7
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Maximilian Arnold101.69
Marc Gauger200.68
Stephan ten Brink32912204.86