Title :
On channel estimation and optimal training for MIMO systems
Author :
Biguesh, Mehrzad ; Gershman, Alex B.
Author_Institution :
Dept. of Commun. Syst., Univ. of Duisburg-Essen, Duisburg, Germany
Abstract :
The performance of MIMO channel estimation methods using training sequences is studied. We consider the popular least squares (LS) and minimum mean-square-error (MMSE) approaches, and propose new scaled LS (SLS) and relaxed minimum mean-square-error (RMMSE) techniques which require less knowledge of the channel second-order statistics and/or have better performance than the LS and MMSE techniques. The optimal choice of training signals is investigated for the aforementioned techniques. In the case of multiple LS channel estimates, the best linear unbiased estimation (BLUE) scheme for their linear combining is proposed and studied.
Keywords :
MIMO systems; channel estimation; least mean squares methods; optimisation; sequences; statistical analysis; BLUE scheme; LS; MIMO system; RMMSE approach; best linear unbiased estimation; channel estimation; least square method; linear combining; optimal training sequence; relaxed minimum mean-square-error; second-order statistics; Array signal processing; Channel estimation; Channel state information; Decoding; Error analysis; Laser sintering; Least squares methods; MIMO; Matrices; Statistics;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2004
Print_ISBN :
0-7803-8545-4
DOI :
10.1109/SAM.2004.1502975
