Computation of Information Rates by means of Discrete States Density Recursion

Starting from the existing works on the computation of information rates of channels with memory, we present a modification of these methods that can be used for continuous-state space models. The principle used for developing this alternative method is based on the partitioning of the continuous-state space into sub-sets, each one representing a state of a trellis, and the association between the states and the probability density functions built and updated on such sub-sets. The paper discusses the cases in which the method provides a computational advantage and it presents numerical results regarding the relevant example of the Wiener phase noise model.