Compensation for signal correlation in multiple-input multiple-output transmitting antenna arrays

A method is implemented to compensate for signal correlation in transmitting antenna arrays of multiple-input multiple-output (MIMO) wireless communication systems. Based on the knowledge of the transmitting channel covariance matrix, a de-correlation transform is designed to remove spatial correlation and antenna mutual coupling in the transmitting antennas. Simulation results show that if there is no correlation in the receiving antennas, this method can be used to realise capacities equivalent to those under the independent and identically distributed (i.i.d.) channel conditions. Results reveal that when there is correlation in the receiving antennas, compensation is more effective when the numbers of elements in the transmitting and receiving arrays are large. For transmitting and receiving arrays with a fixed number of elements, compensation is more effective when the antenna separation is small.

[1]  Hüseyin Arslan,et al.  Dynamics of spatial correlation and implications on MIMO systems , 2004, IEEE Communications Magazine.

[2]  Warren L. Stutzman,et al.  Array antenna pattern modeling methods that include mutual coupling effects , 1993 .

[3]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[4]  Klaus I. Pedersen,et al.  Experimental investigation of correlation properties of MIMO radio channels for indoor picocell scenarios , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[5]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[6]  Michael A. Jensen,et al.  Modeling the indoor MIMO wireless channel , 2002 .

[7]  Per-Simon Kildal,et al.  Correlation and capacity of MIMO systems and mutual coupling, radiation efficiency, and diversity gain of their antennas: simulations and measurements in a reverberation chamber , 2004, IEEE Communications Magazine.

[8]  Roger F. Harrington,et al.  Field computation by moment methods , 1968 .

[9]  Matthias Patzold,et al.  Mobile Fading Channels , 2003 .

[10]  Joseph M. Kahn,et al.  Fading correlation and its effect on the capacity of multielement antenna systems , 2000, IEEE Trans. Commun..

[11]  Chen-Nee Chuah,et al.  Capacity scaling in MIMO Wireless systems under correlated fading , 2002, IEEE Trans. Inf. Theory.

[12]  Michael A. Jensen,et al.  Spatial characteristics of the MIMO wireless channel: experimental data acquisition and analysis , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[13]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .

[14]  Björn E. Ottersten,et al.  Modeling of wide-band MIMO radio channels based on NLoS indoor measurements , 2004, IEEE Transactions on Vehicular Technology.

[15]  Holger Boche,et al.  Channel capacity and capacity-range of beamforming in MIMO wireless systems under correlated fading with covariance feedback , 2004, IEEE Transactions on Wireless Communications.

[16]  Mohamed-Slim Alouini,et al.  Capacity of correlated MIMO Rayleigh channels , 2006, IEEE Transactions on Wireless Communications.

[17]  R. Janaswamy Effect of element mutual coupling on the capacity of fixed length linear arrays , 2002, IEEE Antennas and Wireless Propagation Letters.

[18]  Andrea J. Goldsmith,et al.  Transmitter optimization and optimality of beamforming for multiple antenna systems , 2004, IEEE Transactions on Wireless Communications.