An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Distributed Mobility Management for Target Tracking in Mobile Sensor Networks
IEEE Transactions on Mobile Computing
Distributed Sequential Bayesian Estimation of a Diffusive Source in Wireless Sensor Networks
IEEE Transactions on Signal Processing
Performance Analysis of Distributed Detection in a Random Sensor Field
IEEE Transactions on Signal Processing
Type based estimation over multiaccess channels
IEEE Transactions on Signal Processing
Mutual information and minimum mean-square error in Gaussian channels
IEEE Transactions on Information Theory
Universal decentralized estimation in a bandwidth constrained sensor network
IEEE Transactions on Information Theory
Sequential estimation over noisy channels with distributed node selection
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
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This paper proposes a framework for distributed sequential parameter estimation in wireless sensor networks. In the proposed scheme, the estimator is updated sequentially at the current node with its new measurement and the noisy corrupted local estimator from the previous node. Since all nodes in the network may not carry useful information, methodologies to find the best set of nodes and the corresponding node ordering for the sequential estimation process are investigated. It is shown that the determining the optimal set of nodes that leads to the globally optimal performance is computationally complex when the network size is large. We develop two distributed greedy type node selection algorithms with reduced computational and communication complexities. In these algorithms, the next best node is selected at the current node such that it optimizes a certain reward function. It is shown that the performance of both proposed greed type schemes leads to exact, or close to exact, results to the optimal scheme computed via forward dynamic programming, under certain conditions. Moreover, contrast to existing methodologies, our work considers the node selection and inter-node communication noise jointly in the sequential estimation process.