TY - JOUR
T1 - Optimal step size of the adaptive multichannel LMS algorithm for blind SIMO identification
AU - Huang, Yiteng
AU - Benesty, Jacob
AU - Chen, Jingdong
PY - 2005/3
Y1 - 2005/3
N2 - Adaptive algorithms for blindly identifying single-input multiple-output (SIMO) systems are appealing because of their computational efficiency and capability of continuously tracking a time-varying system. Adaptive multichannel least-mean-square (MCLMS) algorithms (with and without the unit-norm constraint) are analyzed, and the optimal step size is derived. A simple yet effective variable step-size MCLMS algorithm is proposed, and its performance is evaluated with simulations.
AB - Adaptive algorithms for blindly identifying single-input multiple-output (SIMO) systems are appealing because of their computational efficiency and capability of continuously tracking a time-varying system. Adaptive multichannel least-mean-square (MCLMS) algorithms (with and without the unit-norm constraint) are analyzed, and the optimal step size is derived. A simple yet effective variable step-size MCLMS algorithm is proposed, and its performance is evaluated with simulations.
KW - Blind Channel Identification (BCI)
KW - Least Mean Square (LMS)
KW - Multichannel signal processing
KW - SIMO systems
KW - Variable step-size adaptive algorithm
UR - http://www.scopus.com/inward/record.url?scp=14644387516&partnerID=8YFLogxK
U2 - 10.1109/LSP.2004.842286
DO - 10.1109/LSP.2004.842286
M3 - 文章
AN - SCOPUS:14644387516
SN - 1070-9908
VL - 12
SP - 173
EP - 176
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
IS - 3
ER -