Identifiability conditions for blind and semi-blind multichannel estimation

We investigate the identifiability conditions for blind and semi-blind FIR multichannel estimation in terms of channel characteristics, data length and input symbol excitation modes. Parameters are identifiable if they are determined uniquely by the probability distribution of the data. Two models are presented: in the deterministic model, both channel coefficients and input symbols are considered as deterministic quantities and in the Gaussian model, the input symbols as Gaussian random variables. The Gaussian model appears more robust than the deterministic one as it requires less demanding identifiability conditions. Furthermore, semi-blind methods appear superior to blind methods as they allow the estimation of any channel with only few known symbols.