Blind channel estimation exploiting transmission filter knowledge

This contribution elaborates on the concept of blind identification of mult iple FIR channels with transmission filter knowledge (WTXFK). This prior kn owledge could, in fact, include not only the transmitter (TX) (pulse shapin g) filter but also the receiver (RX) filter present in digital communicatio n systems. Exploitation of this side information allows the estimation to c oncentrate on the impulse response of the actual propagation channel itself . Hence this estimation can be done more accurately, Since the prior inform ation is expressed in terms of the channel impulse response, we review a nu mber of blind channel estimation methods that are parameterized directly by the channel and consider their extension to incorporate the prior knowledg e. These methods include essentially subchannel response matching (SRM), su bspace fitting and maximum likelihood (ML) techniques. All these methods ar e formulated for burst mode transmission. We also discuss performance limit s in the form of Cramer-Rao bounds (CRBs). Both the methods and the CRBs ar e discussed in a deterministic and a Gaussian context for the unknown trans mitted symbols. Simulation results indicate that the exploitation of the pr ior knowledge can lead to significant improvements, a capability of the ext ended method to identify ill-conditioned channels, that one particular vers ion SRM WTXFK often outperforms another one, and that ML methods can still further improve performance. (C) 2000 Elsevier Science B.V. All rights rese rved.