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Optimal parameter estimation algorithms are developed using the maximum likelihood technique, when no statistics are available for the parameter. Sub-optimal parameter estimates, using one sample of the autocorrelation of the DFT, have been developed previously. In this paper, maximum likelihood estimates are derived, given the auto-correlation function of the received signal's DFT. These estimates sometimes require less computation time than conventional estimates, and frequently have a closed form or simple iterative implementation.