Mobility

Sequential Estimation Over Noisy Channels With Distributed Node Selection

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Executive Summary

In an autonomous sensor network without a central fusion center, it is desired that any node has the ability to make the final decision once it has enough information about the Phenomenon of Interest (PoI) within a certain confidence level. In this paper, the authors propose a distributed sequential methodology which updates the current node's estimator based on its own observation and noise corrupted decision from the previous node. They show that sequential processing is useful only when the channel quality of inter-sensor communication links satisfies a certain condition. They develop a distributed node selection algorithm to select the order of processing nodes based on information utilities and the communication cost.

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