Predicting CSI for Link Adaptation Employing Support Vector Regression for Channel Extrapolation
Konferenz: WSA 2016 - 20th International ITG Workshop on Smart Antennas
09.03.2016 - 11.03.2016 in München, Deutschland
Tagungsband: WSA 2016
Seiten: 7Sprache: EnglischTyp: PDF
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Autoren:
Djouama, Allaeddine (Department of Electronic Engineering, Chonbuk National University, Korea & Department of Electronic Engineering, University of Science and Technology Houari Boumedien, Algeria)
Zoechmann, Erich (Christian Doppler Laboratory for Dependable Wireless Connectivity for the Society in Motion & Institute of Telecommunications, TU Wien, Austria)
Pratschner, Stefan; Rupp, Markus (Institute of Telecommunications, TU Wien, Austria)
Ettoumi, Fatiha Youcef (Department of Electronic Engineering, University of Science and Technology Houari Boumedien, Algeria)
Inhalt:
Link adaptation in LTE-A is based on channel state information (CSI). For time-selective channels, CSI might be out-dated 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.