Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Optimal dimensionality reduction of sensor data in multisensor estimation fusion
IEEE Transactions on Signal Processing
Distributed Estimation Using Reduced-Dimensionality Sensor Observations
IEEE Transactions on Signal Processing
Bandwidth-constrained distributed estimation for wireless sensor Networks-part I: Gaussian case
IEEE Transactions on Signal Processing
Estimation Diversity and Energy Efficiency in Distributed Sensing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Power scheduling of universal decentralized estimation in sensor networks
IEEE Transactions on Signal Processing
Universal decentralized estimation in a bandwidth constrained sensor network
IEEE Transactions on Information Theory
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We consider distributed estimation of a random scalar parameter in a power constrained wireless sensor network (WSN), where the measurements are sent from the sensors to the fusion center (FC) over noisy wireless channels by employing an analog transmission scheme. We study the power allocation problem with generally correlated sensor observations that can accommodate nonlinear measurement models and spatially correlated observation noise. An effective solution is developed by utilizing a tractable lower bound of the objective function. The proposed algorithm is also extended for random field estimation. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.