Method and apparatus for singular value decomposition of a channel matrix

Abstract

A method and apparatus for decomposing a channel matrix in a wireless communication system are disclosed. A channel matrix H is generated for channels between transmit antennas and receive antennas. A Hermitian matrix A=H H H or A=HH H is created. A Jacobi process is cyclically performed on the matrix A to obtain Q and D A matrixes such that A=QD A Q H . D A is a diagonal matrix obtained by singular value decomposition (SVD) on the A matrix. In each Jacobi transformation, real part diagonalization is performed to annihilate real parts of off-diagonal elements of the matrix and imaginary part diagonalization is performed to annihilate imaginary parts of off-diagonal elements of the matrix after the real part diagonalization. U, V and D H matrixes of H matrix are then calculated from the Q and D A matrices. D H is a diagonal matrix comprising singular values of the H matrix.

1 . A method for decoding data using singular value decomposition (SVD) in a multiple-input multiple-output (MIMO) wireless communication system, the method comprising:
 generating a channel matrix H;   creating a Hermitian matrix A from the matrix H; and,   applying a two-sided Jacobi process cyclically to the matrix A using eigen value decomposition (EVD).   
     
     
         2 . The method of  claim 1  wherein the step (c) comprising:
 performing real part diagonalization of the matrix A; 
 performing imaginary part diagonalization of the matrix A; and, 
 performing fusion of rotation matrices. 
 
     
     
         3 . A receiver for decoding data using singular value decomposition (SVD) in a multiple-input multiple-output (MIMO) wireless communication system, the receiver comprising:
 means for generating a channel matrix H;   means for creating a Hermitian matrix A from the matrix H; and,   means for applying a two-sided Jacobi process cyclically to the matrix A using eigen value decomposition (EVD).   
     
     
         4 . The receiver of  claim 3  wherein the means for applying a two-sided Jacobi process perform real part diagonalization of the matrix A, imaginary part diagonalization of the matrix A and fusion of rotation matrices.