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The optimum sampling in the one- and two-dimensional (1-D and 2-D) Wireless Sensor Networks (WSNs) with spatial-temporally correlated data is studied in this paper. The impacts of the node density in the space domain, the sampling rate in the time domain, and the space-time data correlation on the network performance are investigated asymptotically by considering a large network with infinite area but finite node density and finite temporal sampling rate, under the constraint of fixed power per unit area. The impact of space-time sampling on network performances is investigated in two cases. The first case studies the estimations of the space-time samples collected by the sensors, and the samples are discrete in both the space and time domains.
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