Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Reliability vs. efficiency in distributed source coding for field-gathering sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Spatial correlation-based collaborative medium access control in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Mobile Computing
Distributed sampling for dense sensor networks: a "Bit-conservation principle"
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Impact of Data Retrieval Pattern on Homogeneous Signal Field Reconstruction in Dense Sensor Networks
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Side information aware coding strategies for sensor networks
IEEE Journal on Selected Areas in Communications
On rate-constrained distributed estimation in unreliable sensor networks
IEEE Journal on Selected Areas in Communications
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In this paper, we study the problem of random field estimation with wireless sensor networks. We consider two encoding strategies, namely, Compress-and-Estimate (C&E) and Quantize-and-Estimate (Q&E), which operate with and without side information at the decoder, respectively. We 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); delay-tolerant (DT) networks, where the time horizon is enlarged to a number of consecutive timeslots. For both scenarios and encoding strategies, we extensively analyze the distortion in the reconstructed random field. In DT scenarios, we find closed-form expressions of the optimal number of samples to be encoded in each timeslot (Q&E and C&E cases). Besides, we identify buffer stability conditions and a number of interesting distortion versus buffer occupancy tradeoffs. Latency issues in the reconstruction of the random field are addressed, as well. Computer simulation and numerical results are given in terms of distortion versus number of sensor nodes or SNR, latency versus network size, or buffer occupancy.