Optimal Node Density for Two-Dimensional Sensor Arrays
Information Theory
2016-11-17 v1 math.IT
Abstract
The problem of optimal node density for ad hoc sensor networks deployed for making inferences about two dimensional correlated random fields is considered. Using a symmetric first order conditional autoregressive Gauss-Markov random field model, large deviations results are used to characterize the asymptotic per-node information gained from the array. This result then allows an analysis of the node density that maximizes the information under an energy constraint, yielding insights into the trade-offs among the information, density and energy.
Cite
@article{arxiv.0805.1262,
title = {Optimal Node Density for Two-Dimensional Sensor Arrays},
author = {Youngchul Sung and H. Vincent Poor and Heejung Yu},
journal= {arXiv preprint arXiv:0805.1262},
year = {2016}
}
Comments
Proceedings of the Fifth IEEE Sensor Array and Multichannel Signal Processing Workshop, Darmstadt, Germany, July 21 - 23, 2008