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Optimal Node Density for Two-Dimensional Sensor Arrays (0805.1262v1)
Published 9 May 2008 in cs.IT and 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.