Title :
Adaptive channel SVD estimation for MIMO-OFDM systems
Author :
Zamiri-Jafarian, H. ; Gulak, G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada
fDate :
30 May-1 June 2005
Abstract :
We propose an adaptive estimation algorithm for channel matrix singular value decomposition (SVD) in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The SVD method is an efficient approach to design space-time coding/decoding and detection algorithms in MIMO-OFDM systems. However, the SVD estimation may involve complex nonlinear optimization methods. The proposed algorithm is developed based on a two-step recursive method by utilizing the linear constrained least mean square (LMS) technique.
Keywords :
MIMO systems; OFDM modulation; adaptive estimation; channel estimation; least mean squares methods; optimisation; radio links; recursive estimation; signal detection; singular value decomposition; space-time codes; MIMO-OFDM systems; adaptive channel SVD estimation; adaptive estimation algorithm; channel matrix singular value decomposition; complex nonlinear optimization methods; detection; linear constrained LMS technique; linear constrained least mean square technique; multiple-input multiple-output systems; orthogonal frequency division multiplexing systems; receiving antennas; recursive method; space-time coding; space-time decoding; transmitting antennas; Adaptive estimation; Algorithm design and analysis; Decoding; Detection algorithms; Least squares approximation; MIMO; Matrix decomposition; OFDM; Optimization methods; Singular value decomposition; MIMO channel estimation; MIMO-OFDM systems; SVD estimation; constrained LMS;
Conference_Titel :
Vehicular Technology Conference, 2005. VTC 2005-Spring. 2005 IEEE 61st
Print_ISBN :
0-7803-8887-9
DOI :
10.1109/VETECS.2005.1543352
