Title :
A Joint Blind Channel Order Estimation Algorithm
Author :
Yuhong Wang ; Liang Jin
Author_Institution :
Air Defense Force Acad., Zhengzhou, China
Abstract :
A joint order estimation criterion by combination extreme eigenvalue cost function (deduced from subspace identification) and least squares equalization is proposed, this new criterion ensures the global minimum at the correct and/or effective channel order in noiseless case. For low or moderate SNRs, the joint order estimation algorithm is able to work with short samples and ill-conditioned channels. Simulation results also demonstrate the superiority of this algorithm over other existing methods.
Keywords :
blind equalisers; channel estimation; eigenvalues and eigenfunctions; regression analysis; blind channel equalization method; blind channel identification method; channel order detection; extreme eigenvalue cost function; ill-conditioned channels; joint blind channel order estimation algorithm; joint order estimation criterion; least squares equalization; Channel estimation; Cost function; Eigenvalues and eigenfunctions; Estimation; Joints; Manganese; Signal to noise ratio; blind channel order estimation; extreme eigenvalue cost function; least squares equalization; single-input multiple-outputs; subspace method;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN :
978-1-4799-6928-9
DOI :
10.1109/CICN.2014.242
