QR Decomposition-Based Semi-Blind MIMO Channel Estimation

A novel algorithm is proposed and studied for QR decomposition-based scheme in the context of semi-blind Multi-Input Multi-Output (MIMO) channel estimation. Specifically, the flat-fading MIMO channel matrix H can be decomposed as a down-triangular matrix R and a unitary rotation matrix Q. The matrix R is estimated blindly from only received data by using Cholesky decomposition while the optimum rotation matrix Q is estimated exclusively from training samples based on OPML (Orthogonal Pilot ML Estimator) techniques. Significant estimation gains can be achieved by estimation of such optimum rotation matrices which are parameterized a fewer number of parameters. Furthermore, this semi-blind scheme is shown to be very efficient when the number of receive antennas is greater than the number of transmit antennas, with a low computational cost. Simulation results confirm that the presented estimation based on estimating only the Q matrix from training sequences can perform more efficiently than estimating H directly from the pilot data, and an additional about 4 dB in performance gain would result when exploit 1000 transmitted symbols over Rayleigh fading channels.