Efficient Training of Kalman Algorithm for MIMO Channel Tracking
Conference: European Wireless 2011 - Sustainable Wireless Technologies
04/27/2011 - 04/29/2011 at Vienna, Austria
Proceedings: European Wireless 2011
Pages: 7Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Eitel, Emna; Speidel, Joachim (Institute of Telecommunications, University of Stuttgart, Stuttgart, Germany)
In this paper, a Kalman algorithm is applied to track a time-varying flat fading MIMO channel. The importance of training and appropriate initialization in combination with the Kalman tracking algorithm is shown. Adopting a periodical training scheme with a given bandwidth efficiency, a trade-off between investing pilots for good initialization and training the algorithm exclusively leads to the lowest BER. We also introduce a training on request scheme, in order to overcome the error propagation encountered by the Kalman filter after a series of detection errors. For this purpose, two metrics to detect the Kalman filter divergence are developed.We show the effectiveness of the new aperiodical training scheme in reducing the channel estimation error and saving bandwidth at the same time.