This work investigates a novel semi-blind channel estimation for multiple-input multiple-output （MIMO） space-time block coding （STBC） systems. Algorithms for channel estimation based on whitening-rotation （WR） d...This work investigates a novel semi-blind channel estimation for multiple-input multiple-output （MIMO） space-time block coding （STBC） systems. Algorithms for channel estimation based on whitening-rotation （WR） decomposition that provides a combined quality and spatial scalability is utilized. Using a space-time code-constrained input design, our approach exploits the orthogonality of the signal and noise subspaces in conjunction with orthogonal procrustes （OP） technique to obtain an accurate estimate of the unitary rotation matrix and, consequently, of the channel parameters. Unitary rotation matrices are parameterized a much fewer number of parameters, and significant estimation gains can then be achieved by estimation of such orthogonal matrices. Furthermore, the proposed semi-blind MIMO channel estimation approach is conducted to reduce the complexity of system design when the number of the receive antennas is no less than the number of transmit antennas. Computer simulations are conducted to corroborate the effectiveness of the proposed channel estimation, and they demonstrate the improved performance compared to the existing training-based estimation.展开更多
基金supported by the Scientific Research Foundation for the Digital Multimedia Broadcasting Science, the State Administration of Radio Film and Television (2005-12)
文摘This work investigates a novel semi-blind channel estimation for multiple-input multiple-output （MIMO） space-time block coding （STBC） systems. Algorithms for channel estimation based on whitening-rotation （WR） decomposition that provides a combined quality and spatial scalability is utilized. Using a space-time code-constrained input design, our approach exploits the orthogonality of the signal and noise subspaces in conjunction with orthogonal procrustes （OP） technique to obtain an accurate estimate of the unitary rotation matrix and, consequently, of the channel parameters. Unitary rotation matrices are parameterized a much fewer number of parameters, and significant estimation gains can then be achieved by estimation of such orthogonal matrices. Furthermore, the proposed semi-blind MIMO channel estimation approach is conducted to reduce the complexity of system design when the number of the receive antennas is no less than the number of transmit antennas. Computer simulations are conducted to corroborate the effectiveness of the proposed channel estimation, and they demonstrate the improved performance compared to the existing training-based estimation.
