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.

Computation of information rates by means of discrete states density recursion

REGGIANI, LUCA;
2017-01-01

Abstract

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.
Information rate, Continuous-state channels with memory, Kalman filtering, MIMO channels
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1027039
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