A Joint Blind Channel Order Estimation Algorithm

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.