Estimation from Misaligned Observations with Limited Feedback
Proceedings of the 39th Conference on Information Sciences and Systems (CISS 2005), Baltimore, MD, March 2005.
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Abstract
In remote sensing applications with large numbers of sensors, the global correlation structure of the sensor observations may not be known locally at the sensors. However, some knowledge of this correlation structure can enable the sensors to communicate collaboratively to avoid interference and combat channel noise. A model is proposed for the uncertainty in correlation structure, called a \textit{fading observation model}. An example of multiplicative fading observations with Gaussian sources is analyzed. For this example, the end-to-end distortion scales to $0$ with the number of sensors $M$ like $M^{-1}$ without fading under one scheme, but with fading the same scheme induces a distortion that is bounded away from $0$. A single-bit feedback scheme is proposed to \textit{align} the sensor observations that yields a scaling rate of $M^{-1/3}$. A more complicated class of fading observations for Gaussian sources is described that suggests that relative phase uncertainty is the dominant source of misalignment.
Reference
A.D. Sarwate and M. Gastpar, Estimation from Misaligned Observations with Limited Feedback. Proceedings of the 39th Conference on Information Sciences and Systems (CISS 2005), Baltimore, MD, March 2005.
BibTeX
@INPROCEEDINGS(ads_mg_ciss05, AUTHOR = "A.~D.~Sarwate and M.~Gastpar", TITLE = "Estimation from Misaligned Observations with Limited Feedback", BOOKTITLE = "Proceedings of the 39th Conference on Information Sciences and Systems (CISS 2005)", MONTH = "March", ADDRESS = "Baltimore, MD", YEAR = "2005")