Blind knowledge based algorithms based on second order statistics

Most second order single input multiple output (SIMO) identification algorithms identify the global impulse channel response, convolution of an emission filter and a propagation channel. This paper makes an explicit use of this channel structure in a second order algorithm. We present several structured methods exploiting more or less prior information on the emission filter. Proofs of convergence are provided, and simulations show that some knowledge based algorithms greatly improve over classical blind algorithms, even in the case where the knowledge is partial.