Frequency selective Rician fading MIMO channel and channel Rice factor estimation

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.