Computing the information rate of discrete-time Wiener phase noise channels by parametric Bayesian tracking

A new upper bound (UB) on the information rate (IR) transferred through the additive white Gaussian noise channel affected by Wiener\&\#x02019;s laser phase noise is proposed in the paper. The bound is based on Bayesian tracking of the noisy phase. Specifically, the predictive and posterior densities involved in the tracking are expressed in parametric form, therefore tracking is made on parameters. This make the method less computationally demanding than known non-parametric methods, e.g. methods based on phase quantization and trellis representation of phase memory. Simulation results show that the UB is so close to the lower bound that we can claim of having virtually computed the actual IR.