Title :
On combinations of CMA equalizers
Author :
Candido, Renato ; Silva, Magno T M ; Nascimento, Vítor H.
Author_Institution :
Electron. Syst. Eng. Dept., Univ. of Sao Paulo, Sao Paulo
Abstract :
We extend the affine combination of one fast and one slow least mean-square (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CMA). We analyze the proposed combination in stationary and nonstationary environments verifying that there are situations where the absence of the restriction on the mixing parameter can be advantageous for the combination. Furthermore, we propose a combination of two CMAs with different initializations. Preliminary simulations show that this scheme can avoid local minima and eventually can present a faster convergence rate than that of its components.
Keywords :
adaptive filters; blind equalisers; convergence of numerical methods; least mean squares methods; unsupervised learning; CMA equalizer; LMS filter; adaptive filter; affine combination; blind equalization; constant modulus algorithm; convergence rate; least mean-square method; unsupervised learning; Adaptive equalizers; Adaptive filters; Blind equalizers; Convergence; Delay estimation; Electronic mail; Finite impulse response filter; Least squares approximation; Steady-state; Systems engineering and theory; Adaptive filters; adaptive equalizers; blind equalization; constant modulus algorithm; unsupervised learning;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4960221
