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Abstract

This paper computes the sensing capacity of a sensor network, with sensors of limited range, sensing a two- dimensional Markov random field, by modeling the sensing operation as an encoder. Sensor observations are dependent across sensors, and the sensor network output across different states of the environment is neither identically nor independently distributed. Using a random coding argument, based on the theory of types, we prove a lower bound on the sensing capacity of the network, which characterizes the ability of the sensor network to distinguish among environments with Markov structure, to within a desired accuracy.

Notes

Number of pages: 5

Note: to appear

Text Reference

Yaron Rachlin, R. Negi, and Pradeep Khosla, "Sensing Capacity for Markov Random Fields," International Symposium on Information Theory (ISIT) 2005, 2005.

BibTeX Reference

@inproceedings{Rachlin_2005_5025,
   author = "Yaron Rachlin and R. Negi and Pradeep Khosla",
   title = "Sensing Capacity for Markov Random Fields",
   booktitle = "International Symposium on Information Theory (ISIT) 2005",
   year = "2005",
   Notes = "to appear"
}

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