Tracking and Prediction of Multipath Components in Wireless MIMO Channels

Wireless systems are subject to fading - time variations of the receiving conditions caused by multipath propagation and transceiver movements. Prediction of fading allows to 'learn' the channel state information (CSI) in advance and adjust the transmission scheme accordingly. In this contribution we consider a framework to handle predictions of general fast- and non-flat fading MIMO wireless channels. The approach is based on modeling the dynamics of individual multipath components, extracted with the SAGE algorithm. This decreases the rate of variation of the channel thus allowing a greater prediction horizon and simpler predictor designs. The extracted components are then tracked using dynamical programming coupled with the multipath component distance measure, and component parameters are then predicted over time using adaptive predictors - hypermodels. We consider linear as well as nonlinear predictor designs. This prediction scheme is applied to MIMO impulse response measurements in 2 GHz frequency band, tracked over the distance of ap 4 m, achieving prediction horizons of 1.5lambda.

[1]  Hao Ling,et al.  Prediction of fast fading mobile radio channels in wideband communication systems , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[2]  Harry L. Van Trees,et al.  Optimum Array Processing , 2002 .

[3]  Frank Frederiksen,et al.  Prediction of future fading based on past measurements , 1999, Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324).

[4]  H. Hallen,et al.  Physical channel modeling, adaptive prediction and transmitter diversity for flat fading mobile channel , 1999, 1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304).

[5]  Alexandra Duel-Hallen,et al.  Deterministic channel modeling and long range prediction of fast fading mobile radio channels , 1998, IEEE Communications Letters.

[6]  T. Ekman,et al.  Nonlinear prediction of mobile radio channels: measurements and MARS model designs , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[7]  Andrew Harvey,et al.  Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .

[8]  Rodney G. Vaughan,et al.  Short-term mobile channel prediction using discrete scatterer propagation model and subspace signal processing algorithms , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[9]  S. Haykin.  Kalman Filtering and Neural Networks , 2001 .

[10]  Andreas F. Molisch,et al.  Wireless Communications , 2005 .

[11]  D. Hampicke,et al.  Identification of time-variant directional mobile radio channels , 1999, IMTC/99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309).

[12]  Hamdy A. Taha,et al.  Operations Research , 1971 .

[13]  Jeng-Kuang Hwang,et al.  Sinusoidal modeling and prediction of fast fading processes , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[14]  Ernst Bonek.  Double-Directional Superresolution Radio Channel Measurements , 2001 .

[15]  T. Moon,et al.  Mathematical Methods and Algorithms for Signal Processing , 1999 .

[16]  Douglas D. O'Shaughnessy,et al.  Speech communication : human and machine , 1987 .

[17]  Thomas Kailath,et al.  Detection of signals by information theoretic criteria , 1985, IEEE Trans. Acoust. Speech Signal Process..

[18]  Ernst Bonek,et al.  How to Quantify Multipath Separation , 2002 .

[19]  Torbjörn Ekman.  Prediction of Mobile Radio Channels : Modeling and Design , 2002 .

[20]  M. Viberg,et al.  Two decades of array signal processing research: the parametric approach , 1996, IEEE Signal Process. Mag..

[21]  Kapil R. Dandekar,et al.  Vector channel modeling and prediction for the improvement of downlink received power , 2002, IEEE Trans. Commun..

[22]  Hans D. Hallen,et al.  Long-range prediction of fading signals , 2000, IEEE Signal Process. Mag..

[23]  Klaus I. Pedersen,et al.  Channel parameter estimation in mobile radio environments using the SAGE algorithm , 1999, IEEE J. Sel. Areas Commun..