Home > Timetable > Contribution details
PDF | XML | iCal

Bayesian Inference in Digital Communication.Part II: Applications

Presented by Luca BARLETTA on 15 Oct 2012 from 16:20 to 18:20
Track: bayesian inference


A classical problem in synchronization, an activity that plays a central role in signal processing for digital communication, is that of extracting the phase of a sinusoid affected by phase noise and embedded in additive noise. In the talk, the problem is presented as an instance of Bayesian inference. Four variants of the basic problem are treated. 1) Sinusoid with constant amplitude, where the phase is extracted by filtering the sinusoid through the Wiener filter. 2) Sinusoid affected by known amplitude modulation. Here the system model is no more stationary, and the phase should be extracted by filtering the sinusoid through the Kalman filter. 3) Sinusoid affected by unknown amplitude modulation. Here non-parametric methods, such as quantization of the phase space, should be adopted. 4) A message is transmitted through a channel that includes up/down conversion, that is multiplication of the message by a sinusoid. In this context, the phase noise affecting the sinusoid is a source of disturbance that compromises channel capacity. Computation of channel capacity can be approached by Bayesian methods that track the phase noise that affect the sinusoid.


Location: EGO, Cascina
Address: The European Gravitational Observatory (http://www.ego-gw.it), site of the Virgo interferometer, is located in the countryside of the Comune of Cascina, a few kilometres from town of Pisa.
Room: Auditorium