Talks and Poster Presentations (with Proceedings-Entry):
A. Djouama, E. Zöchmann, S. Pratschner, M. Rupp, F. Ettoumi:
"Predicting CSI for Link Adaptation Employing Support Vector Regression for Channel Extrapolation";
Poster: Workshop on Smart Antennas,
München;
03-09-2016
- 03-11-2016; in: "WSA 2016",
VDE Verlag GmbH,
Berlin
(2016),
ISBN: 978-3-8007-4177-9;
380
- 386.
English abstract:
Link adaptation in LTE-A is based on channel state
information (CSI). For time-selective channels, CSI might be outdated
already in the next subframe. Hence, CSI prediction must
be employed. This paper investigates support vector regression
(SVR) for channel extrapolation and prediction. SVR is applied
for learning from the previous channel estimates in order to
predict the CSI of the following ones. Simulation results show
that the proposed method performs better than simple linear
prediction methods and close to minimum mean square error
prediction especially in a reasonable signal to noise ratio regime.
Keywords:
Support Vector Machines, Channel Estimation, LTE, MMSE, interpolation, extrapolation, CSI prediction
Electronic version of the publication:
http://publik.tuwien.ac.at/files/PubDat_248531.pdf
Created from the Publication Database of the Vienna University of Technology.