Analysis of a Decision-Directed Receiver for a Markov Sequence with Unknown Transition Probabilities

In many applications, such as in video transmission, the data can be modeled as a Markov sequence and the performance of the detector improved through incorporation of the transition probabilities into the threshold. The difficulty in implementation is that the transition probabilities are often unknown or known imprecisely. In this paper, a decision-directed receiver (DDR) is analyzed which estimates these transition probabilities. This is an extension of recently reported work where the data consisted of an independent sequence with unknown priors.