Optimum delay and sequence estimation from incomplete data

An easily implementable dynamic programming algorithm that estimates sequences and timing delay jointly from the contaminated decision statistics available to the receiver is introduced. Although the algorithm is optimal in a joint maximum-likelihood sense, given the observed data, it is not globally optimal, since the observed data do not constitute a sufficient statistic in the absence of synchronization. On the other hand, the observed data are simple to collect, the receiver is simple to implement, and the performance obtained is robust to timing errors. Moreover, the simplicity of the observed data makes the receiver easily implementable digitally, and the need for a separate synchronizer is obviated