Synchronization of superimposed training for channel estimation

Channel estimation for single-input multiple-output (SIMO) time-invariant or slowly time-varying channels was recently considered in (J. K. Tugnait et al, IEEE Comm. Lett., vol.CL-8, p.413-415, 2003) using superimposed training. A periodic (non-random) training sequence is arithmetically added (superimposed) at a low power to the information sequence at the transmitter before modulation and transmission. In the Tugnait method, the channel is estimated using only the first-order statistics of the data, under the assumption that the superimposed training sequence at the receiver is time-synchronized with its transmitted counterpart. In this paper, we remove this assumption of synchronization and propose a novel approach to superimposed training synchronization. An illustrative computer simulation example is presented.