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ICASSP
2011
IEEE

The Bayesian inference of phase

12 years 7 months ago
The Bayesian inference of phase
Bayesian recursive inference of phase in additive Gaussian noise environments is studied. A tractable conjugate system is established using a von Mises distribution. Its shaping parameter, κ, is studied, to reveal the link with classical phase estimation via matched transforms. Uncertainty quantifiers involve a modified Bessel function kernel. The optimal predictor of data is derived in the presence of phase uncertainty. The theory is applied in phase synchronization for a digital receiver, where phase is distributed as a mixture of von Mises. A fully Bayesian treatment of the decoding problem for phase-uncertain carriers results. Simulation results provide evidence for the improvement in accuracy over a certainty-equivalent-based prediction.
Anthony Quinn, Jean-Pierre Barbot, Pascal Larzabal
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Anthony Quinn, Jean-Pierre Barbot, Pascal Larzabal
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