How Much Information Can One Get From a Wireless Ad Hoc Sensor Network Over a Correlated Random Field?

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Executive Summary

New large deviations results that characterize the asymptotic information rates for general d-Dimensional (d-D) stationary Gaussian fields are obtained. By applying the general results to sensor nodes on a Two-Dimensional (2-D) lattice, the asymptotic behavior of ad hoc sensor networks deployed over correlated random fields for statistical inference is investigated. Under a 2-D hidden Gauss-Markov random field model with symmetric first order conditional autoregression and the assumption of no in-network data fusion, the behavior of the total obtainable information [nats] and energy efficiency [nats/J] defined as the ratio of total gathered information to the required energy is obtained as the coverage area, node density and energy vary.

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