Paper Info
Title
Frequency selective Rician fading MIMO channel and channel Rice factor estimation
Abstract
In this paper, to estimate Rician frequency selective fading Multiple-Input Multiple-Output (MIMO) channels, the Shifted Scaled Least Squares (SSLS) and General form of the Linear Minimum Mean Square Error (GLMMSE) channel estimators are proposed. It is shown that these estimators achieve much better minimum possible Bayesian Cramér-Rao Lower Bounds (CRLBs) in the frequency selective Rician fading MIMO channels compared with those of the Rayleigh one. Numerical examples show that the performance of these estimators is not more sensitive to accurate estimation of the channel Rice factor. Furthermore, to estimate the channel Rice factor at the receiver, we propose two new algorithms which perform based on the Least Squares (LS) estimates and training sequences. Simulation results confirm the efficiency of these algorithms.
Year
DOI
Venue
2010
10.1109/WCSP.2010.5633539
WCSP
Keywords
Field
DocType
bayes methods,mimo communication,rician channels,channel estimation,least squares approximations,mean square error methods,bayesian cramér-rao lower bounds,channel rice factor estimation,frequency selective rician fading mimo channel,general form,least squares estimation,linear minimum mean square error channel estimator,multiple-input multiple-output channels,shifted scaled least squares,training sequences,frequency selective rician fading,generalized lmmse,mimo,estimation,lower bound,least square,fading
Least squares,Fading,Minimum mean square error,Algorithm,MIMO,Communication channel,Real-time computing,Statistics,Mathematics,Estimator,Rician fading,Bayesian probability
Conference
ISBN
Citations 
PageRank 
978-1-4244-7554-4
0
0.34
References 
Authors
9
2
Name
Order
Citations
PageRank
Moghaddam, S.S.100.68
Hamid Nooralizadeh241.44