Robust Training Sequence Design for Spatially Correlated MIMO Channel Estimation

A robust superimposed training sequence design is proposed for spatially correlated multiple-input-multiple-output (MIMO) channel estimation. The proposed scheme does not require accurate knowledge of the spatial correlation matrix, and it is shown to outperform previously proposed robust correlated MIMO channel estimators, such as relaxed minimum mean square error (RMMSE) and least-square RMMSE. Since the training sequence is overlaid into the data stream, the spectral efficiency of the system is higher than those that use time-multiplexed pilots. A solution for the sequence can easily be obtained by using a projection on convex-set-based iterative algorithm that is guaranteed to converge as long as the training sequence matrix is initialized to have full rank. Furthermore, it is shown that the proposed scheme is identical to the RMMSE-based schemes when the MIMO channel is spatially uncorrelated. The computational complexity of the proposed algorithm is also illustrated.

[1]  Yu Ted Su,et al.  MIMO channel estimation in spatially correlated environments , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[2]  Behrouz Farhang-Boroujeny,et al.  Pilot-based channel identification: proposal for semi-blind identification of communication channels , 1995 .

[3]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[4]  Ha H. Nguyen,et al.  Optimal Superimposed Training Design for Spatially Correlated Fading MIMO Channels , 2008, IEEE Transactions on Wireless Communications.

[5]  Jitendra K. Tugnait,et al.  On channel estimation using superimposed training and first-order statistics , 2003, IEEE Communications Letters.

[6]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[7]  Akbar M. Sayeed,et al.  Transmit signal design for optimal estimation of correlated MIMO channels , 2004, IEEE Transactions on Signal Processing.

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

[9]  Ha H. Nguyen,et al.  Orthogonal Affine Precoding and Decoding for Channel Estimation and Source Detection in MIMO Frequency-Selective Fading Channels , 2009, IEEE Transactions on Signal Processing.

[10]  Kim-Chuan Toh,et al.  On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0 , 2012 .

[11]  Liuqing Yang,et al.  Optimal training for MIMO frequency-selective fading channels , 2005, IEEE Transactions on Wireless Communications.

[12]  Sailes K. Sengijpta.  Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[13]  Hamid Jafarkhani,et al.  Multiple transmit antenna differential detection from generalized orthogonal designs , 2001, IEEE Trans. Inf. Theory.

[14]  J.H. Manton,et al.  Orthogonal superimposed training on linear precoding: a new affine precoder design , 2005, IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, 2005..

[15]  M. Viberg,et al.  Superimposed periodic pilots for blind channel estimation , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[16]  Thomas L. Marzetta,et al.  Unitary space-time modulation for multiple-antenna communications in Rayleigh flat fading , 2000, IEEE Trans. Inf. Theory.

[17]  Desmond C. McLernon,et al.  Channel estimation using implicit training , 2004, IEEE Transactions on Signal Processing.

[18]  Branka Vucetic,et al.  Space-Time Coding , 2003 .

[19]  Georgios B. Giannakis,et al.  Optimal training and redundant precoding for block transmissions with application to wireless OFDM , 2002, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[20]  G. Matz,et al.  Improved MMSE estimation of correlated MIMO channels using a structured correlation estimator , 2005, IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, 2005..

[21]  Babak Hassibi,et al.  How much training is needed in multiple-antenna wireless links? , 2003, IEEE Trans. Inf. Theory.

[22]  Brian L. Hughes,et al.  Differential space-time modulation , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[23]  M. Kießling,et al.  MIMO channel estimation in correlated fading environments , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[24]  Alex B. Gershman,et al.  Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals , 2006, IEEE Transactions on Signal Processing.

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

[26]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[27]  Branka Vucetic,et al.  Space-Time Coding , 2003 .

[28]  D. Youla,et al.  Image Restoration by the Method of Convex Projections: Part 1ߞTheory , 1982, IEEE Transactions on Medical Imaging.

[29]  V. Koivunen,et al.  Channel estimation and tracking in spatially correlated MIMO OFDM systems , 2003, IEEE Workshop on Statistical Signal Processing, 2003.

[30]  Markku J. Juntti,et al.  Space-time channel estimation and performance analysis for wireless MIMO-OFDM systems with spatial correlation , 2005, IEEE Transactions on Vehicular Technology.

[31]  T. Forshaw.  Everything you always wanted to know , 1977 .

[32]  Lang Tong,et al.  Channel estimation for space-time orthogonal block codes , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[33]  Hamid Jafarkhani,et al.  A differential detection scheme for transmit diversity , 2000, IEEE Journal on Selected Areas in Communications.