A CORRELATION TENSOR – BASED MODEL FOR TIME VARIANT FREQUENC Y SELECTIVE MIMO CHANNELS

In this contribution we present a new analytical channel model for frequency selective, time variant MIMO systems. The model is based on a correlation tensor, which allows a natural description of multi–dimensional signals. By appl ying the Higher Order Singular Value Decomposition (HOSVD), we gain a better insight into the multi–dimensional eigenstructure of the channel. Applications of the model include the denoising of measured channels and the possibility to generate new synthetic channels displaying a give n correlation in time, frequency, and space. The proposed model possesses advantages over existing 2–dimensional ei genmode–based channel models. In contrast to them, the tensor–based model can cope with frequency and time selectivity in a natural way.

[1]  Chen-Nee Chuah,et al.  Capacity of multi-antenna array systems in indoor wireless environment , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[2]  S. Haykin,et al.  A Novel Wideband MIMO Channel Model and McMaster's Wideband MIMO SDR , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[3]  Ernst Bonek,et al.  A stochastic MIMO channel model with joint correlation of both link ends , 2006, IEEE Transactions on Wireless Communications.

[4]  Martin Haardt,et al.  A subspace-based channel model for frequency selective time variant MIMO channels , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[5]  Martin Haardt,et al.  Geometry-based channel modelling of MIMO channels in comparison with channel sounder measurements , 2005 .

[6]  M. Haardt,et al.  Higher Order SVD Based Subspace Estimation to Improve Multi-Dimensional Parameter Estimation Algorithms , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.