The overall system efficiency of impulse radio communications relies critically on judicious allocation of transmission resources, a portion of which should be used to ensure successful timing acquisition. In data-aided mode, optimum timing offset estimation depends not only on the mechanism used for energy capture and the acquisition algorithm employed to recover timing information, but also on the training sequence (TS) pattern from which the timing information is to be extracted. Furthermore, the transmission resources used for timing have to be balanced with that for conveying information messages in order to strike desirable tradeoffs between timing accuracy and information rate. In Part I of this paper, data-aided timing offset estimation is derived based on the maximum likelihood (ML) criterion, where only symbol-rate samples are needed for low-complexity receiver processing. To minimize the mean-square timing errors of these ML synchronizers while at the same time maximizing the average system capacity, TS design and transmit power allocation are investigated in this paper. The optimum training pattern and the number, placement, and power distribution between training and information-bearing symbols are formulated as a resource allocation optimization problem whose solution optimizes system-level performance with the minimum amount of resources consumed.