Quantize-and-Estimate encoding schemes for random field estimation with delay-constrained and delay-tolerant wireless sensor networks

In this paper, we study the problem of random field estimation with wireless sensor networks. We adopt a Quantize-and-Estimate encoding scheme and focus our attention on two scenarios of interest: delay-constrained networks, in which the observations collected in a particular timeslot must be immediately encoded and conveyed to the Fusion Center (FC); and delay-tolerant (DT) networks, where the time horizon is enlarged to a number of consecutive timeslots. For both scenarios, we extensively analyze the distortion in the reconstructed random field. In the DT scenario, we find the closed-form expression of the optimal number of samples to be encoded in each timeslot. Besides, we also address latency issues in the reconstruction of the random field. Computer simulation and numerical results are given in terms of distortion vs. number of sensor nodes or SNR and, latency vs. network size.